Qualitative reasoning uses incomplete knowledge to compute a description of the possible behaviors for dynamic systems. A standard qualitative simulation（QSIM） algorithm frequently results in a large number of incom...Qualitative reasoning uses incomplete knowledge to compute a description of the possible behaviors for dynamic systems. A standard qualitative simulation（QSIM） algorithm frequently results in a large number of incomprehensible behavioral descriptions and the simulation for complex systems frequently is intractable. Two model de- composition methods are proposed in this paper to eliminate or decrease the insujficiency of this algorithm. Using a directed graph to represent the qualitative model, the strongly connected graph based theory and genetic algorithm based model decomposition are proposed to decompose the model. A new simple system model is reconstructed by subgraphs and causal relations when the system directed graph is decomposed completely. Each sub-graph is viewed as a separate system and will be simulated separately, and the simulation result of causally upstream subsystem is used to constrain the behavior of downstream subsystems. The model decomposition algorithm provides a promising paradigm for qualitative simulation whose complexity is driven by the complexity of the problem specification rather than the inference mechanism used.展开更多
The objective of reliability-based design optimization(RBDO)is to minimize the optimization objective while satisfying the corresponding reliability requirements.However,the nested loop characteristic reduces the effi...The objective of reliability-based design optimization(RBDO)is to minimize the optimization objective while satisfying the corresponding reliability requirements.However,the nested loop characteristic reduces the efficiency of RBDO algorithm,which hinders their application to high-dimensional engineering problems.To address these issues,this paper proposes an efficient decoupled RBDO method combining high dimensional model representation(HDMR)and the weight-point estimation method(WPEM).First,we decouple the RBDO model using HDMR and WPEM.Second,Lagrange interpolation is used to approximate a univariate function.Finally,based on the results of the first two steps,the original nested loop reliability optimization model is completely transformed into a deterministic design optimization model that can be solved by a series of mature constrained optimization methods without any additional calculations.Two numerical examples of a planar 10-bar structure and an aviation hydraulic piping system with 28 design variables are analyzed to illustrate the performance and practicability of the proposed method.展开更多
A decomposition model was applied to study the resource-saving and environment-friendly effects of air pollutant emissions(taking industrial SO2 emission as an example) in China.From the results,it is found that 38.93...A decomposition model was applied to study the resource-saving and environment-friendly effects of air pollutant emissions(taking industrial SO2 emission as an example) in China.From the results,it is found that 38.93% and 61.07% are contributed to environment-friendly and resource-saving effects,respectively,by the dramatic decrease in industrial SO2 emission density(nearly 70% from 2001 to 2010).This indicates that China has achieved important progress during the 11th FYP(five-year plan) compared with the 10th FYP.A simultaneous equations model was also employed to analyze the influencing factors by using data from 30 provinces in China.The results imply that the influence of environmental regulation on environment-friendly effect is not obvious during the 10th FYP but obvious during the 11th FYP.Thus,the government should continue promoting the environment-friendly effect by further enhancing environmental regulation and strengthening the role of environmental management.展开更多
COVID-19 has caused severe health complications and produced a substantial adverse economic impact around the world.Forecasting the trend of COVID-19 infections could help in executing policies to effectively reduce t...COVID-19 has caused severe health complications and produced a substantial adverse economic impact around the world.Forecasting the trend of COVID-19 infections could help in executing policies to effectively reduce the number of new cases.In this study,we apply the decomposition and ensemble model to forecast COVID-19 confirmed cases,deaths,and recoveries in Pakistan for the upcoming month until the end of July.For the decomposition of data,the Ensemble Empirical Mode Decomposition(EEMD)technique is applied.EEMD decomposes the data into small components,called Intrinsic Mode Functions(IMFs).For individual IMFs modelling,we use the Autoregressive Integrated Moving Average(ARIMA)model.The data used in this study is obtained from the official website of Pakistan that is publicly available and designated for COVID-19 outbreak with daily updates.Our analyses reveal that the number of recoveries,new cases,and deaths are increasing in Pakistan exponentially.Based on the selected EEMD-ARIMA model,the new confirmed cases are expected to rise from 213,470 to 311,454 by 31 July 2020,which is an increase of almost 1.46 times with a 95%prediction interval of 246,529 to 376,379.The 95%prediction interval for recovery is 162,414 to 224,579,with an increase of almost two times in total from 100802 to 193495 by 31 July 2020.On the other hand,the deaths are expected to increase from 4395 to 6751,which is almost 1.54 times,with a 95%prediction interval of 5617 to 7885.Thus,the COVID-19 forecasting results of Pakistan are alarming for the next month until 31 July 2020.They also confirm that the EEMD-ARIMA model is useful for the short-term forecasting of COVID-19,and that it is capable of keeping track of the real COVID-19 data in nearly all scenarios.The decomposition and ensemble strategy can be useful to help decision-makers in developing short-term strategies about the current number of disease occurrences until an appropriate vaccine is developed.展开更多
High resolution image fusion is a significant focus in the field of image processing. A new image fusion model is presented based on the characteristic level of empirical mode decomposition （EMD）. The intensity hue ...High resolution image fusion is a significant focus in the field of image processing. A new image fusion model is presented based on the characteristic level of empirical mode decomposition （EMD）. The intensity hue saturation （IHS） transform of the multi-spectral image first gives the intensity image. Thereafter, the 2D EMD in terms of row-column extension of the 1D EMD model is used to decompose the detailed scale image and coarse scale image from the high-resolution band image and the intensity image. Finally, a fused intensity image is obtained by reconstruction with high frequency of the high-resolution image and low frequency of the intensity image and IHS inverse transform result in the fused image. After presenting the EMD principle, a multi-scale decomposition and reconstruction algorithm of 2D EMD is defined and a fusion technique scheme is advanced based on EMD. Panchromatic band and multi-spectral band 3,2,1 of Quickbird are used to assess the quality of the fusion algorithm. After selecting the appropriate intrinsic mode function （IMF） for the merger on the basis of EMD analysis on specific row （column） pixel gray value series, the fusion scheme gives a fused image, which is compared with generally used fusion algorithms （wavelet, IHS, Brovey）. The objectives of image fusion include enhancing the visibility of the image and improving the spatial resolution and the spectral information of the original images. To assess quality of an image after fusion, information entropy and standard deviation are applied to assess spatial details of the fused images and correlation coefficient, bias index and warping degree for measuring distortion between the original image and fused image in terms of spectral information. For the proposed fusion algorithm, better results are obtained when EMD algorithm is used to perform the fusion experience.展开更多
Through the matching relationship between land use types and carbon emission items, this paper estimated carbon emissions of different land use types in Nanjing City, China and analyzed the influencing factors of carb...Through the matching relationship between land use types and carbon emission items, this paper estimated carbon emissions of different land use types in Nanjing City, China and analyzed the influencing factors of carbon emissions by Logarithmic Mean Divisia Index（LMDI） model. The main conclusions are as follows： 1） Total anthropogenic carbon emission of Nanjing increased from 1.22928 ×10^7 t in 2000 to 3.06939 × 10^7 t in 2009, in which the carbon emission of Inhabitation, mining ＆ manufacturing land accounted for 93% of the total. 2） The average land use carbon emission intensity of Nanjing in 2009 was 46.63 t/ha, in which carbon emission intensity of Inhabitation, mining ＆ manufacturing land was the highest（200.52 t/ha）, which was much higher than that of other land use types. 3） The average carbon source intensity in Nanjing was 16 times of the average carbon sink intensity（2.83 t/ha） in 2009, indicating that Nanjing was confronted with serious carbon deficit and huge carbon cycle pressure. 4） Land use area per unit GDP was an inhibitory factor for the increase of carbon emissions, while the other factors were all contributing factors. 5） Carbon emission effect evaluation should be introduced into land use activities to formulate low-carbon land use strategies in regional development.展开更多
Background:Litter traits critically affect litter decomposition from local to global scales.However,our understanding of the temporal dynamics of litter trait-decomposition linkages,especially their dependence on plan...Background:Litter traits critically affect litter decomposition from local to global scales.However,our understanding of the temporal dynamics of litter trait-decomposition linkages,especially their dependence on plant functional type remains limited.Methods:We decomposed the leaf litter of 203 tree species that belong to two different functional types(deciduous and evergreen)for 2 years in a subtropical forest in China.The Weibull residence model was used to describe the different stages of litter decomposition by calculating the time to 10%,25%and 50%mass loss(Weibull t_(1/10),t_(1/4),and t_(1/2)respectively)and litter mean residence time(Weibull MRT).The resulting model parameters were used to explore the control of litter traits(e.g.,N,P,condensed tannins and tensile strength)over leaf litter decomposition across different decomposition stages.Results:The litter traits we measured had lower explanatory power for the early stages(Weibull t_(1/10)and t_(1/4))than for the later stages(Weibull t_(1/2)and MRT)of decomposition.The relative importance of different types of litter traits in influencing decomposition changed dramatically during decomposition,with physical traits exerting predominant control for the stages of Weibull t_(1/10)and MRT and nutrient-related traits for the stages of Weibull t_(1/4),and t_(1/2).Moreover,we found that litter decomposition of the early three stages(Weibull t_(1/10),t_(1/4),and t_(1/2))of the two functional types was controlled by different types of litter traits;that is,the litter decomposition rates of deciduous species were predominately controlled by nutrient-related traits,while the litter decomposition rates of evergreen species were mainly controlled by carbon-related traits.Conclusions:This study suggests that litter trait-decomposition linkages vary with decomposition stages and are strongly mediated by plant functional type,highlighting the necessity to consider their temporal dynamics and plant functional types for improving predictions of litter decomposition.展开更多
Previous studies revealed that the error of pole coordinate prediction will significantly increase for a prediction period longer than 100 days, and this is mainly caused by short period oscillations. Empirical mode d...Previous studies revealed that the error of pole coordinate prediction will significantly increase for a prediction period longer than 100 days, and this is mainly caused by short period oscillations. Empirical mode decomposition （EMD）, which is increasingly popular and has advantages over classical wavelet decomposition, can be used to remove short period variations from observed time series of pole co- ordinates. A hybrid model combing EMD and extreme learning machine （ELM）, where high frequency signals are removed and processed time series is then modeled and predicted, is summarized in this paper. The prediction performance of the hybrid model is compared with that of the ELM-only method created from original time series. The results show that the proposed hybrid model outperforms the pure ELM method for both short-term and long-term prediction of pole coordinates. The improvement of prediction accuracy up to 360 days in the future is found to be 24.91% and 26.79% on average in terms of mean absolute error （MAE） for the xp and yp components of pole coordinates, respectively.展开更多
This paper discusses comparison of two time series decomposition methods: The Least Squares Estimation (LSE) and Buys-Ballot Estimation (BBE) methods. As noted by Iwueze and Nwogu (2014), there exists a research gap f...This paper discusses comparison of two time series decomposition methods: The Least Squares Estimation (LSE) and Buys-Ballot Estimation (BBE) methods. As noted by Iwueze and Nwogu (2014), there exists a research gap for the choice of appropriate model for decomposition and detection of presence of seasonal effect in a series model. Estimates of trend parameters and seasonal indices are all that are needed to fill the research gap. However, these estimates are obtainable through the Least Squares Estimation (LSE) and Buys-Ballot Estimation (BBE) methods. Hence, there is need to compare estimates of the two methods and recommend. The comparison of the two methods is done using the Accuracy Measures (Mean Error (ME)), Mean Square Error (MSE), the Mean Absolute Error (MAE), and the Mean Absolute Percentage Error (MAPE). The results from simulated series show that for the additive model;the summary statistics (ME, MSE and MAE) for the two estimation methods and for all the selected trending curves are equal in all the simulations both in magnitude and direction. For the multiplicative model, results show that when a series is dominated by trend, the estimates of the parameters by both methods become less precise and differ more widely from each other. However, if conditions for successful transformation (using the logarithmic transform in linearizing the multiplicative model to additive model) are met, both of them give similar results.展开更多
To maintain healthy and sanitary indoor air quality, development of effective decontamination measures for the indoor environment is important and hydrogen peroxide is often used as decontamination agent in healthcare...To maintain healthy and sanitary indoor air quality, development of effective decontamination measures for the indoor environment is important and hydrogen peroxide is often used as decontamination agent in healthcare environment. In this study, we focused on the decomposition phenomena of vaporized hydrogen peroxide on wall surfaces in indoor environment and discussed a wall surface decomposition model for vaporized hydrogen peroxide using computational fluid dynamics to simulate the concentration distributions of vaporized hydrogen peroxide. A major drawback to using numerical simulations is the lack of sufficient data on boundary conditions for various types of building materials and hence. We also conducted the fundamental chamber experiment to identify the model parameters of wall surface decomposition model for targeting five types of building materials.展开更多
A method for simultaneous determination of mixed model parameters,which have different physical dimensions or different responses to data,is presented.Mixed parameter estimation from observed data within a single mode...A method for simultaneous determination of mixed model parameters,which have different physical dimensions or different responses to data,is presented.Mixed parameter estimation from observed data within a single model space shows instabilities and trade-offs of the solutions. We separate the model space into N-subspaces based on their physical properties or computational convenience and solve the N-subspaces systems by damped least-squares and singular-value decomposition. Since the condition number of each subsystem is smaller than that of the single global system,the approach can greatly increase the stability of the inversion. We also introduce different damping factors into the subsystems to reduce the tradeoffs between the different parameters. The damping factors depend on the conditioning of the subsystems and may be adequately chosen in a range from 0.1 % to 10 % of the largest singular value. We illustrate the method with an example of simultaneous determination of source history,source geometry,and hypocentral location from regional seismograms,although it is applicable to any geophysical inversion.展开更多
Forecasting returns for the Artificial Intelligence and Robotics Index is of great significance for financial market stability,and the development of the artificial intelligence industry.To provide investors with a mo...Forecasting returns for the Artificial Intelligence and Robotics Index is of great significance for financial market stability,and the development of the artificial intelligence industry.To provide investors with a more reliable reference in terms of artificial intelligence index investment,this paper selects the NASDAQ CTA Artificial Intelligence and Robotics(AIRO)Index as the research target,and proposes innovative hybrid methods to forecast returns by considering its multiple structural characteristics.Specifically,this paper uses the ensemble empirical mode decomposition(EEMD)method and the modified iterative cumulative sum of squares(ICSS)algorithm to decompose the index returns and identify the structural breakpoints.Furthermore,it combines the least-square support vector machine approach with the particle swarm optimization method(PSO-LSSVM)and the generalized autoregressive conditional heteroskedasticity(GARCH)type models to construct innovative hybrid forecasting methods.On the one hand,the empirical results indicate that the AIRO index returns have complex structural characteristics,and present time-varying and nonlinear characteristics with high complexity and mutability;on the other hand,the newly proposed hybrid forecasting method(i.e.,the EEMD-PSO-LSSVM-ICSS-GARCH models)which considers these complex structural characteristics,can yield the optimal forecasting performance for the AIRO index returns.展开更多
Contrary to the aliasing defect between the adjacent intrinsic model functions(IMFs) existing in empirical model decomposition(EMD), a new method of detecting dynamic unbalance with cardan shaft in high-speed train wa...Contrary to the aliasing defect between the adjacent intrinsic model functions(IMFs) existing in empirical model decomposition(EMD), a new method of detecting dynamic unbalance with cardan shaft in high-speed train was proposed by applying the combination between EMD, Hankel matrix, singular value decomposition(SVD) and normalized Hilbert transform(NHT). The vibration signals of gimbal installed base were decomposed through EMD to get different IMFs. The Hankel matrix constructed through the single IMF was orthogonally executed through SVD. The critical singular values were selected to reconstruct vibration signs on the basis of the key stack of singular values. Instantaneous frequencys(IFs) of reconstructed vibration signs were applied to detect dynamic unbalance with shaft and eliminated clutter spectrum caused by the aliasing defect between the adjacent IMFs, which highlighted the failure characteristics. The method was verified by test data in the unbalance condition of dynamic cardan shaft. The results show that the method effectively detects the fault vibration characteristics caused by cardan shaft dynamic unbalance and extracts the nature vibration features. With comparison to the traditional EMD-NHT, clarity and failure characterization force are significantly improved.展开更多
A decentralized adaptive neural network sliding mode position/force control scheme is proposed for constrained reconfigurable manipulators. Different from the decentralized control strategy in multi-manipulator cooper...A decentralized adaptive neural network sliding mode position/force control scheme is proposed for constrained reconfigurable manipulators. Different from the decentralized control strategy in multi-manipulator cooperation, the proposed decentralized position/force control scheme can be applied to series constrained reconfigurable manipulators. By multiplying each row of Jacobian matrix in the dynamics by contact force vector, the converted joint torque is obtained. Furthermore, using desired information of other joints instead of their actual values, the dynamics can be represented as a set of interconnected subsystems by model decomposition technique. An adaptive neural network controller is introduced to approximate the unknown dynamics of subsystem. The interconnection and the whole error term are removed by employing an adaptive sliding mode term. And then, the Lyapunov stability theory guarantees the stability of the closed-loop system. Finally, two reconfigurable manipulators with different configurations are employed to show the effectiveness of the proposed decentralized position/force control scheme.展开更多
Based on the decomposition model of environmental quality and univariate regression model,the relationships of industrial wastewater drainage with economic scale,economic structure,and technological level in Anshan,a ...Based on the decomposition model of environmental quality and univariate regression model,the relationships of industrial wastewater drainage with economic scale,economic structure,and technological level in Anshan,a mining city in Northeast China,were studied. The results showed that,due to scale effect,the drainage of three important industrial wastewater pollutants(COD,NH3-N and petroleum) increased 8505t,671t and 384t,respectively,and due to structure effect,those pollutants drainage increased 3996t,174t and 120t from 2001 to 2006. While due to technological effect,the drainage of COD,NH3-N and petroleum reduced 4452t,458t and 331t,and due to cross effect,those pollutants drainage reduced 7270t,575t and 476t simultaneously. Meantime,the relationships between household consumption structure and domestic sewage discharge were analyzed,and domestic sewage discharges in different income levels were also compared. The results showed that,the domestic sewage discharges would increase 376t with 1000 yuan(RMB) increased in the traffic and communication consumption,and they would be 344t,219t,428t,1873t,respectively,in housing consumption,food consumption,medical consumption,miscellaneous commodity consumption. The proportion of domestic sewage discharge increased for high income residents significantly,but reduced for lower income residents. The industrial wastewater pollutants drainage tends to be reduced by technical progress,while domestic sewage discharge will be a more important factor for urban water environment quality.展开更多
Background： Forestry offers possibilities to sequestrate carbon in living biomass, deadwood and forest soil, as we as in products prepared of wood. In addition, the use of wood may reduce carbon emissions from fossil...Background： Forestry offers possibilities to sequestrate carbon in living biomass, deadwood and forest soil, as we as in products prepared of wood. In addition, the use of wood may reduce carbon emissions from fossil fuels. However, harvesting decreases the carbon stocks of forests and increases emissions from decomposing harvest residues. Methods： This study used simulation and optimization to maximize carbon sequestration in a boreal forest estate consisting of nearly 600 stands. A reference management plan maximized net present value and the other plans maximized the total carbon balance of a 100-, 200- or 300-year planning horizon, taking into account the carbon balances of living forest biomass, dead organic matter, and wood-based products Results： Maximizing carbon balance led to low cutting level with all three planning horizons. Depending on the time span, the carbon balance of these schedules was 2 to 3.5 times higher than in the plan that maximized net present value. It was not optimal to commence cuttings when the carbon pool of living biomass and dead organic matter stopped increasing after 150-200 years. Conclusions： Letting many mature trees to die was a better strategy than harvesting them when the aim was to maximize the long-term carbon balance of boreal Fennoscandian forest. The reason for this conclusion was that large dead trees are better carbon stores than harvested trees. To alter this outcome, a higher proportion of harvested trees should be used for products in which carbon is stored for long time.展开更多
External electric field(EEF)has shown its advantages in tuning chemical reaction as an efficient and fea-sible-to-control tool.In this paper,we explored the mechanisms of three EEF-rerulated Diels-Alder reactions in-c...External electric field(EEF)has shown its advantages in tuning chemical reaction as an efficient and fea-sible-to-control tool.In this paper,we explored the mechanisms of three EEF-rerulated Diels-Alder reactions in-cluding two traditional-DA reactions to form two C-C single bonds and a hetero-DA reaction to form both a c and a CO bond,respectively,and introduced an EEF contribution decomposition(ECD)model to understand how the EEF coupled with the intrinsic nuclear and electronic redistributions so as to affect chemical reaction.The ECD model,by decomposing the overall EEF effects into geometry re-equilibrium and static induction parts,can give a clear and quantitative picture of a physical quantity change upon EEF,as demonstrated on relative energies,activa-tion barriers,charge distribution and dipole moments.The ECD analvses will shed light on the effective tuning of chemical reactions by the elestric field.展开更多
Due to the increasing complexity of products and for the distributed product development, more closely collaborative work among designers is required. A collaborative assembly planning approach is proposed to support ...Due to the increasing complexity of products and for the distributed product development, more closely collaborative work among designers is required. A collaborative assembly planning approach is proposed to support assembly planning in a networked environment. The working procedure is depicted and the key techniques including collaborative-planning-oriented assembly decomposition modeling, assembly assignment modeling, and sub-plans merging are addressed. By incorporating visual models at client side with assembly application models at server side, a web-based supporting environment for collaborative assembly planning has been developed using VRML and Java-EAI techniques. A case study is given to illustrate the feasibility and validity of the idea.展开更多
This paper proposes two concepts: the ecological footprint component index(EFCI) and the biocapacity component index(BCCI), based on the ecological footprint(EF) and Shannon entropy approaches. Per capita EFCI and BCC...This paper proposes two concepts: the ecological footprint component index(EFCI) and the biocapacity component index(BCCI), based on the ecological footprint(EF) and Shannon entropy approaches. Per capita EFCI and BCCI in China 1949-2013 are analyzed using empirical mode decomposition(EMD). Nonlinear models of per capita EFCI and BCCI in China 1949-2013 are presented and their cycles and predictions from 2014 to 2023 are analyzed. The results over the last 65 years show:(1) EFCI in China has increased constantly with fluctuations, while BCCI has slowly decreased. Their annual change rates are 2.81% and-1.26%, respectively. The increasing EFCI indicates a gradual improvement in China's sustainable development potential; the decreasing BCCI indicates severe environmental and population challenges.(2) The cycles of per capita EFCI have periods of 5.4 and 16.3 years, while cycles of per capita BCCI have periods of 3.6, 13,and 21.7 years. The predictive models indicate that EFCI will first decrease, reaching 0.02725 in2014, and will subsequently increase to 0.03261 in 2021. BCCI will increase, reaching 0.01365 in2014 and 0.01541 in 2022. EFCI and BCCI will reach 0.03037 and 0.01537, respectively, in 2023.Policymakers should ensure that the EFCI and BCCI increase in 2023.展开更多
In the context of ＂two-wheel drive＂ development mode, China＇s construction land shows significant expansion characteristics. The carbon emission effect of construction land changes is an important factor for the in...In the context of ＂two-wheel drive＂ development mode, China＇s construction land shows significant expansion characteristics. The carbon emission effect of construction land changes is an important factor for the increase of carbon emissions in the atmosphere. In this study, the drivers of carbon emissions in Anhui Province from 1997 to 2011 were quantitatively measured using the improved Kaya identity and Logarithmic Mean Divisia Index. The results show that： economic growth, expansion of construction land and changes in population density have incremental effects on carbon emissions. The average contribution rate of economic growth as the first driver is 266.32 percent. The construction land expansion is an important driving factor with annual mean carbon effect of 6.4057 million tons and annual mean contribution rate of 187.30 percent. But the change in population density has little impact on carbon emission driving. Energy structure changes and energy intensity reduction have inhibitory effects on carbon emissions, of which the annual mean contribution rate is -212.06 percent and -158.115 percent respectively. The targeted policy approaches of carbon emission reduction were put forward based on the decomposition of carbon emission factors, laying a scientific basis to rationally use the land for the Government, which is conducive to build an ecological province for Anhui and achieve the purpose of emission reduction, providing a reference for the research on carbon emission effect of changes in provincial-scale construction land.展开更多
文摘Qualitative reasoning uses incomplete knowledge to compute a description of the possible behaviors for dynamic systems. A standard qualitative simulation（QSIM） algorithm frequently results in a large number of incomprehensible behavioral descriptions and the simulation for complex systems frequently is intractable. Two model de- composition methods are proposed in this paper to eliminate or decrease the insujficiency of this algorithm. Using a directed graph to represent the qualitative model, the strongly connected graph based theory and genetic algorithm based model decomposition are proposed to decompose the model. A new simple system model is reconstructed by subgraphs and causal relations when the system directed graph is decomposed completely. Each sub-graph is viewed as a separate system and will be simulated separately, and the simulation result of causally upstream subsystem is used to constrain the behavior of downstream subsystems. The model decomposition algorithm provides a promising paradigm for qualitative simulation whose complexity is driven by the complexity of the problem specification rather than the inference mechanism used.
基金supported by the Innovation Fund Project of the Gansu Education Department(Grant No.2021B-099).
文摘The objective of reliability-based design optimization(RBDO)is to minimize the optimization objective while satisfying the corresponding reliability requirements.However,the nested loop characteristic reduces the efficiency of RBDO algorithm,which hinders their application to high-dimensional engineering problems.To address these issues,this paper proposes an efficient decoupled RBDO method combining high dimensional model representation(HDMR)and the weight-point estimation method(WPEM).First,we decouple the RBDO model using HDMR and WPEM.Second,Lagrange interpolation is used to approximate a univariate function.Finally,based on the results of the first two steps,the original nested loop reliability optimization model is completely transformed into a deterministic design optimization model that can be solved by a series of mature constrained optimization methods without any additional calculations.Two numerical examples of a planar 10-bar structure and an aviation hydraulic piping system with 28 design variables are analyzed to illustrate the performance and practicability of the proposed method.
基金Project(201009066)supported by the R&D Special Fund for Public Welfare of the Ministry of Finance and Ministry of Science and Technology of China
文摘A decomposition model was applied to study the resource-saving and environment-friendly effects of air pollutant emissions(taking industrial SO2 emission as an example) in China.From the results,it is found that 38.93% and 61.07% are contributed to environment-friendly and resource-saving effects,respectively,by the dramatic decrease in industrial SO2 emission density(nearly 70% from 2001 to 2010).This indicates that China has achieved important progress during the 11th FYP(five-year plan) compared with the 10th FYP.A simultaneous equations model was also employed to analyze the influencing factors by using data from 30 provinces in China.The results imply that the influence of environmental regulation on environment-friendly effect is not obvious during the 10th FYP but obvious during the 11th FYP.Thus,the government should continue promoting the environment-friendly effect by further enhancing environmental regulation and strengthening the role of environmental management.
文摘COVID-19 has caused severe health complications and produced a substantial adverse economic impact around the world.Forecasting the trend of COVID-19 infections could help in executing policies to effectively reduce the number of new cases.In this study,we apply the decomposition and ensemble model to forecast COVID-19 confirmed cases,deaths,and recoveries in Pakistan for the upcoming month until the end of July.For the decomposition of data,the Ensemble Empirical Mode Decomposition(EEMD)technique is applied.EEMD decomposes the data into small components,called Intrinsic Mode Functions(IMFs).For individual IMFs modelling,we use the Autoregressive Integrated Moving Average(ARIMA)model.The data used in this study is obtained from the official website of Pakistan that is publicly available and designated for COVID-19 outbreak with daily updates.Our analyses reveal that the number of recoveries,new cases,and deaths are increasing in Pakistan exponentially.Based on the selected EEMD-ARIMA model,the new confirmed cases are expected to rise from 213,470 to 311,454 by 31 July 2020,which is an increase of almost 1.46 times with a 95%prediction interval of 246,529 to 376,379.The 95%prediction interval for recovery is 162,414 to 224,579,with an increase of almost two times in total from 100802 to 193495 by 31 July 2020.On the other hand,the deaths are expected to increase from 4395 to 6751,which is almost 1.54 times,with a 95%prediction interval of 5617 to 7885.Thus,the COVID-19 forecasting results of Pakistan are alarming for the next month until 31 July 2020.They also confirm that the EEMD-ARIMA model is useful for the short-term forecasting of COVID-19,and that it is capable of keeping track of the real COVID-19 data in nearly all scenarios.The decomposition and ensemble strategy can be useful to help decision-makers in developing short-term strategies about the current number of disease occurrences until an appropriate vaccine is developed.
文摘High resolution image fusion is a significant focus in the field of image processing. A new image fusion model is presented based on the characteristic level of empirical mode decomposition （EMD）. The intensity hue saturation （IHS） transform of the multi-spectral image first gives the intensity image. Thereafter, the 2D EMD in terms of row-column extension of the 1D EMD model is used to decompose the detailed scale image and coarse scale image from the high-resolution band image and the intensity image. Finally, a fused intensity image is obtained by reconstruction with high frequency of the high-resolution image and low frequency of the intensity image and IHS inverse transform result in the fused image. After presenting the EMD principle, a multi-scale decomposition and reconstruction algorithm of 2D EMD is defined and a fusion technique scheme is advanced based on EMD. Panchromatic band and multi-spectral band 3,2,1 of Quickbird are used to assess the quality of the fusion algorithm. After selecting the appropriate intrinsic mode function （IMF） for the merger on the basis of EMD analysis on specific row （column） pixel gray value series, the fusion scheme gives a fused image, which is compared with generally used fusion algorithms （wavelet, IHS, Brovey）. The objectives of image fusion include enhancing the visibility of the image and improving the spatial resolution and the spectral information of the original images. To assess quality of an image after fusion, information entropy and standard deviation are applied to assess spatial details of the fused images and correlation coefficient, bias index and warping degree for measuring distortion between the original image and fused image in terms of spectral information. For the proposed fusion algorithm, better results are obtained when EMD algorithm is used to perform the fusion experience.
基金Under the auspices of National Natural Science Foundation of China(No.41301633)National Social Science Foundation of China(No.10ZD&030)+1 种基金Postdoctoral Science Foundation of China(No.2012M511243,2013T60518)Clean Development Mechanism Foundation of China(No.1214073,2012065)
文摘Through the matching relationship between land use types and carbon emission items, this paper estimated carbon emissions of different land use types in Nanjing City, China and analyzed the influencing factors of carbon emissions by Logarithmic Mean Divisia Index（LMDI） model. The main conclusions are as follows： 1） Total anthropogenic carbon emission of Nanjing increased from 1.22928 ×10^7 t in 2000 to 3.06939 × 10^7 t in 2009, in which the carbon emission of Inhabitation, mining ＆ manufacturing land accounted for 93% of the total. 2） The average land use carbon emission intensity of Nanjing in 2009 was 46.63 t/ha, in which carbon emission intensity of Inhabitation, mining ＆ manufacturing land was the highest（200.52 t/ha）, which was much higher than that of other land use types. 3） The average carbon source intensity in Nanjing was 16 times of the average carbon sink intensity（2.83 t/ha） in 2009, indicating that Nanjing was confronted with serious carbon deficit and huge carbon cycle pressure. 4） Land use area per unit GDP was an inhibitory factor for the increase of carbon emissions, while the other factors were all contributing factors. 5） Carbon emission effect evaluation should be introduced into land use activities to formulate low-carbon land use strategies in regional development.
基金supported by the National Natural Science Foundation of China(Grant Nos.31830015 and 32171752)。
文摘Background:Litter traits critically affect litter decomposition from local to global scales.However,our understanding of the temporal dynamics of litter trait-decomposition linkages,especially their dependence on plant functional type remains limited.Methods:We decomposed the leaf litter of 203 tree species that belong to two different functional types(deciduous and evergreen)for 2 years in a subtropical forest in China.The Weibull residence model was used to describe the different stages of litter decomposition by calculating the time to 10%,25%and 50%mass loss(Weibull t_(1/10),t_(1/4),and t_(1/2)respectively)and litter mean residence time(Weibull MRT).The resulting model parameters were used to explore the control of litter traits(e.g.,N,P,condensed tannins and tensile strength)over leaf litter decomposition across different decomposition stages.Results:The litter traits we measured had lower explanatory power for the early stages(Weibull t_(1/10)and t_(1/4))than for the later stages(Weibull t_(1/2)and MRT)of decomposition.The relative importance of different types of litter traits in influencing decomposition changed dramatically during decomposition,with physical traits exerting predominant control for the stages of Weibull t_(1/10)and MRT and nutrient-related traits for the stages of Weibull t_(1/4),and t_(1/2).Moreover,we found that litter decomposition of the early three stages(Weibull t_(1/10),t_(1/4),and t_(1/2))of the two functional types was controlled by different types of litter traits;that is,the litter decomposition rates of deciduous species were predominately controlled by nutrient-related traits,while the litter decomposition rates of evergreen species were mainly controlled by carbon-related traits.Conclusions:This study suggests that litter trait-decomposition linkages vary with decomposition stages and are strongly mediated by plant functional type,highlighting the necessity to consider their temporal dynamics and plant functional types for improving predictions of litter decomposition.
基金supported by Chinese Academy of Sciences(No.201491)“Light of West China” Program(201491)
文摘Previous studies revealed that the error of pole coordinate prediction will significantly increase for a prediction period longer than 100 days, and this is mainly caused by short period oscillations. Empirical mode decomposition （EMD）, which is increasingly popular and has advantages over classical wavelet decomposition, can be used to remove short period variations from observed time series of pole co- ordinates. A hybrid model combing EMD and extreme learning machine （ELM）, where high frequency signals are removed and processed time series is then modeled and predicted, is summarized in this paper. The prediction performance of the hybrid model is compared with that of the ELM-only method created from original time series. The results show that the proposed hybrid model outperforms the pure ELM method for both short-term and long-term prediction of pole coordinates. The improvement of prediction accuracy up to 360 days in the future is found to be 24.91% and 26.79% on average in terms of mean absolute error （MAE） for the xp and yp components of pole coordinates, respectively.
文摘This paper discusses comparison of two time series decomposition methods: The Least Squares Estimation (LSE) and Buys-Ballot Estimation (BBE) methods. As noted by Iwueze and Nwogu (2014), there exists a research gap for the choice of appropriate model for decomposition and detection of presence of seasonal effect in a series model. Estimates of trend parameters and seasonal indices are all that are needed to fill the research gap. However, these estimates are obtainable through the Least Squares Estimation (LSE) and Buys-Ballot Estimation (BBE) methods. Hence, there is need to compare estimates of the two methods and recommend. The comparison of the two methods is done using the Accuracy Measures (Mean Error (ME)), Mean Square Error (MSE), the Mean Absolute Error (MAE), and the Mean Absolute Percentage Error (MAPE). The results from simulated series show that for the additive model;the summary statistics (ME, MSE and MAE) for the two estimation methods and for all the selected trending curves are equal in all the simulations both in magnitude and direction. For the multiplicative model, results show that when a series is dominated by trend, the estimates of the parameters by both methods become less precise and differ more widely from each other. However, if conditions for successful transformation (using the logarithmic transform in linearizing the multiplicative model to additive model) are met, both of them give similar results.
文摘To maintain healthy and sanitary indoor air quality, development of effective decontamination measures for the indoor environment is important and hydrogen peroxide is often used as decontamination agent in healthcare environment. In this study, we focused on the decomposition phenomena of vaporized hydrogen peroxide on wall surfaces in indoor environment and discussed a wall surface decomposition model for vaporized hydrogen peroxide using computational fluid dynamics to simulate the concentration distributions of vaporized hydrogen peroxide. A major drawback to using numerical simulations is the lack of sufficient data on boundary conditions for various types of building materials and hence. We also conducted the fundamental chamber experiment to identify the model parameters of wall surface decomposition model for targeting five types of building materials.
基金supported by Innovation Project of Chinese Academy of Sciences
文摘A method for simultaneous determination of mixed model parameters,which have different physical dimensions or different responses to data,is presented.Mixed parameter estimation from observed data within a single model space shows instabilities and trade-offs of the solutions. We separate the model space into N-subspaces based on their physical properties or computational convenience and solve the N-subspaces systems by damped least-squares and singular-value decomposition. Since the condition number of each subsystem is smaller than that of the single global system,the approach can greatly increase the stability of the inversion. We also introduce different damping factors into the subsystems to reduce the tradeoffs between the different parameters. The damping factors depend on the conditioning of the subsystems and may be adequately chosen in a range from 0.1 % to 10 % of the largest singular value. We illustrate the method with an example of simultaneous determination of source history,source geometry,and hypocentral location from regional seismograms,although it is applicable to any geophysical inversion.
基金support from National Natural Science Foundation of China(Nos.71774051,72243003)National Social Science Fund of China(No.22AZD128)the seminar participants in Center for Resource and Environmental Management,Hunan University,China.
文摘Forecasting returns for the Artificial Intelligence and Robotics Index is of great significance for financial market stability,and the development of the artificial intelligence industry.To provide investors with a more reliable reference in terms of artificial intelligence index investment,this paper selects the NASDAQ CTA Artificial Intelligence and Robotics(AIRO)Index as the research target,and proposes innovative hybrid methods to forecast returns by considering its multiple structural characteristics.Specifically,this paper uses the ensemble empirical mode decomposition(EEMD)method and the modified iterative cumulative sum of squares(ICSS)algorithm to decompose the index returns and identify the structural breakpoints.Furthermore,it combines the least-square support vector machine approach with the particle swarm optimization method(PSO-LSSVM)and the generalized autoregressive conditional heteroskedasticity(GARCH)type models to construct innovative hybrid forecasting methods.On the one hand,the empirical results indicate that the AIRO index returns have complex structural characteristics,and present time-varying and nonlinear characteristics with high complexity and mutability;on the other hand,the newly proposed hybrid forecasting method(i.e.,the EEMD-PSO-LSSVM-ICSS-GARCH models)which considers these complex structural characteristics,can yield the optimal forecasting performance for the AIRO index returns.
基金Projects(61134002,51305358)supported by the National Natural Science Foundation of ChinaProject(PIL1303)supported by the Open Project of State Key Laboratory of Precision Measurement Technology and Instruments,ChinaProject(2682014BR032)supported by the Fundamental Research Funds for the Central Universities,China
文摘Contrary to the aliasing defect between the adjacent intrinsic model functions(IMFs) existing in empirical model decomposition(EMD), a new method of detecting dynamic unbalance with cardan shaft in high-speed train was proposed by applying the combination between EMD, Hankel matrix, singular value decomposition(SVD) and normalized Hilbert transform(NHT). The vibration signals of gimbal installed base were decomposed through EMD to get different IMFs. The Hankel matrix constructed through the single IMF was orthogonally executed through SVD. The critical singular values were selected to reconstruct vibration signs on the basis of the key stack of singular values. Instantaneous frequencys(IFs) of reconstructed vibration signs were applied to detect dynamic unbalance with shaft and eliminated clutter spectrum caused by the aliasing defect between the adjacent IMFs, which highlighted the failure characteristics. The method was verified by test data in the unbalance condition of dynamic cardan shaft. The results show that the method effectively detects the fault vibration characteristics caused by cardan shaft dynamic unbalance and extracts the nature vibration features. With comparison to the traditional EMD-NHT, clarity and failure characterization force are significantly improved.
基金Project(61374051,61603387)supported by the National Natural Science Foundation of ChinaProjects(20150520112JH,20160414033GH)supported by the Scientific and Technological Development Plan in Jilin Province of ChinaProject(20150102)supported by Opening Funding of State Key Laboratory of Management and Control for Complex Systems,China
文摘A decentralized adaptive neural network sliding mode position/force control scheme is proposed for constrained reconfigurable manipulators. Different from the decentralized control strategy in multi-manipulator cooperation, the proposed decentralized position/force control scheme can be applied to series constrained reconfigurable manipulators. By multiplying each row of Jacobian matrix in the dynamics by contact force vector, the converted joint torque is obtained. Furthermore, using desired information of other joints instead of their actual values, the dynamics can be represented as a set of interconnected subsystems by model decomposition technique. An adaptive neural network controller is introduced to approximate the unknown dynamics of subsystem. The interconnection and the whole error term are removed by employing an adaptive sliding mode term. And then, the Lyapunov stability theory guarantees the stability of the closed-loop system. Finally, two reconfigurable manipulators with different configurations are employed to show the effectiveness of the proposed decentralized position/force control scheme.
基金Under the auspices of Major State Basic Research Development Program of China (No. 2004CB418507)
文摘Based on the decomposition model of environmental quality and univariate regression model,the relationships of industrial wastewater drainage with economic scale,economic structure,and technological level in Anshan,a mining city in Northeast China,were studied. The results showed that,due to scale effect,the drainage of three important industrial wastewater pollutants(COD,NH3-N and petroleum) increased 8505t,671t and 384t,respectively,and due to structure effect,those pollutants drainage increased 3996t,174t and 120t from 2001 to 2006. While due to technological effect,the drainage of COD,NH3-N and petroleum reduced 4452t,458t and 331t,and due to cross effect,those pollutants drainage reduced 7270t,575t and 476t simultaneously. Meantime,the relationships between household consumption structure and domestic sewage discharge were analyzed,and domestic sewage discharges in different income levels were also compared. The results showed that,the domestic sewage discharges would increase 376t with 1000 yuan(RMB) increased in the traffic and communication consumption,and they would be 344t,219t,428t,1873t,respectively,in housing consumption,food consumption,medical consumption,miscellaneous commodity consumption. The proportion of domestic sewage discharge increased for high income residents significantly,but reduced for lower income residents. The industrial wastewater pollutants drainage tends to be reduced by technical progress,while domestic sewage discharge will be a more important factor for urban water environment quality.
文摘Background： Forestry offers possibilities to sequestrate carbon in living biomass, deadwood and forest soil, as we as in products prepared of wood. In addition, the use of wood may reduce carbon emissions from fossil fuels. However, harvesting decreases the carbon stocks of forests and increases emissions from decomposing harvest residues. Methods： This study used simulation and optimization to maximize carbon sequestration in a boreal forest estate consisting of nearly 600 stands. A reference management plan maximized net present value and the other plans maximized the total carbon balance of a 100-, 200- or 300-year planning horizon, taking into account the carbon balances of living forest biomass, dead organic matter, and wood-based products Results： Maximizing carbon balance led to low cutting level with all three planning horizons. Depending on the time span, the carbon balance of these schedules was 2 to 3.5 times higher than in the plan that maximized net present value. It was not optimal to commence cuttings when the carbon pool of living biomass and dead organic matter stopped increasing after 150-200 years. Conclusions： Letting many mature trees to die was a better strategy than harvesting them when the aim was to maximize the long-term carbon balance of boreal Fennoscandian forest. The reason for this conclusion was that large dead trees are better carbon stores than harvested trees. To alter this outcome, a higher proportion of harvested trees should be used for products in which carbon is stored for long time.
基金Supported by the National Natural Science Foundation of China(Nos.21873060,21473107)the Fundamental Researcl Funds for the Central Universities of China(No.GK201901007)。
文摘External electric field(EEF)has shown its advantages in tuning chemical reaction as an efficient and fea-sible-to-control tool.In this paper,we explored the mechanisms of three EEF-rerulated Diels-Alder reactions in-cluding two traditional-DA reactions to form two C-C single bonds and a hetero-DA reaction to form both a c and a CO bond,respectively,and introduced an EEF contribution decomposition(ECD)model to understand how the EEF coupled with the intrinsic nuclear and electronic redistributions so as to affect chemical reaction.The ECD model,by decomposing the overall EEF effects into geometry re-equilibrium and static induction parts,can give a clear and quantitative picture of a physical quantity change upon EEF,as demonstrated on relative energies,activa-tion barriers,charge distribution and dipole moments.The ECD analvses will shed light on the effective tuning of chemical reactions by the elestric field.
基金This research is supported by National Nature Science Foundation of China (NSFC) under the project number 59990470-2.
文摘Due to the increasing complexity of products and for the distributed product development, more closely collaborative work among designers is required. A collaborative assembly planning approach is proposed to support assembly planning in a networked environment. The working procedure is depicted and the key techniques including collaborative-planning-oriented assembly decomposition modeling, assembly assignment modeling, and sub-plans merging are addressed. By incorporating visual models at client side with assembly application models at server side, a web-based supporting environment for collaborative assembly planning has been developed using VRML and Java-EAI techniques. A case study is given to illustrate the feasibility and validity of the idea.
基金supported by the Opening Foundation of Jiangsu Key Laboratory of Environment Change&Ecological ConstructionNational Natural Science Foundation of China:[Grant Number 41372182]Research Center of Resource-exhausted Cities Transformation and Development:[Grant Number Kf2013y08]
文摘This paper proposes two concepts: the ecological footprint component index(EFCI) and the biocapacity component index(BCCI), based on the ecological footprint(EF) and Shannon entropy approaches. Per capita EFCI and BCCI in China 1949-2013 are analyzed using empirical mode decomposition(EMD). Nonlinear models of per capita EFCI and BCCI in China 1949-2013 are presented and their cycles and predictions from 2014 to 2023 are analyzed. The results over the last 65 years show:(1) EFCI in China has increased constantly with fluctuations, while BCCI has slowly decreased. Their annual change rates are 2.81% and-1.26%, respectively. The increasing EFCI indicates a gradual improvement in China's sustainable development potential; the decreasing BCCI indicates severe environmental and population challenges.(2) The cycles of per capita EFCI have periods of 5.4 and 16.3 years, while cycles of per capita BCCI have periods of 3.6, 13,and 21.7 years. The predictive models indicate that EFCI will first decrease, reaching 0.02725 in2014, and will subsequently increase to 0.03261 in 2021. BCCI will increase, reaching 0.01365 in2014 and 0.01541 in 2022. EFCI and BCCI will reach 0.03037 and 0.01537, respectively, in 2023.Policymakers should ensure that the EFCI and BCCI increase in 2023.
基金the Key Research Fund of Anhui Provincial Education Department (No.2010sk502zd)the National Natural Science Foundation of China (No.41071337)
文摘In the context of ＂two-wheel drive＂ development mode, China＇s construction land shows significant expansion characteristics. The carbon emission effect of construction land changes is an important factor for the increase of carbon emissions in the atmosphere. In this study, the drivers of carbon emissions in Anhui Province from 1997 to 2011 were quantitatively measured using the improved Kaya identity and Logarithmic Mean Divisia Index. The results show that： economic growth, expansion of construction land and changes in population density have incremental effects on carbon emissions. The average contribution rate of economic growth as the first driver is 266.32 percent. The construction land expansion is an important driving factor with annual mean carbon effect of 6.4057 million tons and annual mean contribution rate of 187.30 percent. But the change in population density has little impact on carbon emission driving. Energy structure changes and energy intensity reduction have inhibitory effects on carbon emissions, of which the annual mean contribution rate is -212.06 percent and -158.115 percent respectively. The targeted policy approaches of carbon emission reduction were put forward based on the decomposition of carbon emission factors, laying a scientific basis to rationally use the land for the Government, which is conducive to build an ecological province for Anhui and achieve the purpose of emission reduction, providing a reference for the research on carbon emission effect of changes in provincial-scale construction land.
