The evolutionary strategy with a dynamic weighting schedule is proposed to find all the compromised solutions of the multi-objective integrated structure and control optimization problem, where the optimal system perf...The evolutionary strategy with a dynamic weighting schedule is proposed to find all the compromised solutions of the multi-objective integrated structure and control optimization problem, where the optimal system performance and control cost are defined by H2 or H∞ norms. During this optimization process, the weights are varying with the increasing generation instead of fixed values. The proposed strategy together with the linear matrix inequality （LMI） or the Riccati controller design method can find a series of uniformly distributed nondominated solutions in a single run. Therefore, this method can greatly reduce the computation intensity of the integrated optimization problem compared with the weight-based single objective genetic algorithm. Active automotive suspension is adopted as an example to illustrate the effectiveness of the proposed method.展开更多
In the present study,multimodel ensemble forecast experiments of the global horizontal irradiance(GHI)were conducted using the dynamic variable weight technique.The study was based on the forecasts of four numerical m...In the present study,multimodel ensemble forecast experiments of the global horizontal irradiance(GHI)were conducted using the dynamic variable weight technique.The study was based on the forecasts of four numerical models,namely,the China Meteorological Administration Wind Energy and Solar Energy Prediction System,the Mesoscale Weather Numerical Prediction System of China Meteorological Administration,the China Meteorological Administration Regional Mesoscale Numerical Prediction System-Guangdong,and the Weather Research and Forecasting Model-Solar,and observational data from four photovoltaic(PV)power stations in Yangjiang City,Guangdong Province.The results show that compared with those of the monthly optimal numerical model forecasts,the dynamic variable weight-based ensemble forecasts exhibited 0.97%-15.96%smaller values of the mean absolute error and 3.31%-18.40%lower values of the root mean square error(RMSE).However,the increase in the correlation coefficient was not obvious.Specifically,the multimodel ensemble mainly improved the performance of GHI forecasts below 700 W m^(-2),particularly below 400 W m^(-2),with RMSE reductions as high as 7.56%-28.28%.In contrast,the RMSE increased at GHI levels above 700 W m^(-2).As for the key period of PV power station output(02:00-07:00),the accuracy of GHI forecasts could be improved by the multimodel ensemble:the multimodel ensemble could effectively decrease the daily maximum absolute error(AE max)of GHI forecasts.Moreover,with increasing forecasting difficulty under cloudy conditions,the multimodel ensemble,which yields data closer to the actual observations,could simulate GHI fluctuations more accurately.展开更多
Using the RFM(Recency,Frequency,Monetary value)model can provide valuable insights about customer clusterswhich is the core of customer relationship management.Due to accurate customer segment coming from dynamic weig...Using the RFM(Recency,Frequency,Monetary value)model can provide valuable insights about customer clusterswhich is the core of customer relationship management.Due to accurate customer segment coming from dynamic weighted applications,in-depth targeted marketing may also use type of dynamic weight of R,F and M as factors.In this paper,we present our dynamic weighted RFM approach which is intended to improve the performance of customer segmentation by using the factors and variations to attain dynamic weights.Our dynamic weight approach is a kind of Custom method in essential which roots in the understanding of the data set.Firstly,Analytic Hierarchy Process is used to calculate the subjective weight,then the entropy method is applied to calculate the objective weight.Finally,we use comprehensive integration weighting method to combine the subjective and objective weight to obtain the final weight of the index to calculate the individual user value and quantify the user value difference.The experiment shows that the dynamic weight we used in RFM model is vital,affects the customer segmentation performance positively.Also,this study indicates that customer segments containing dynamic weighted RFM scores bring about stronger and more accurate association rules for the understanding of customer behavior.At last,we discuss the limitations of RFM analysis.展开更多
To improve the performance of multiple classifier system, a knowledge discovery based dynamic weighted voting （KD-DWV） is proposed based on knowledge discovery. In the method, all base classifiers may be allowed to ...To improve the performance of multiple classifier system, a knowledge discovery based dynamic weighted voting （KD-DWV） is proposed based on knowledge discovery. In the method, all base classifiers may be allowed to operate in different measurement/feature spaces to make the most of diverse classification information. The weights assigned to each output of a base classifier are estimated by the separability of training sample sets in relevant feature space. For this purpose, some decision tables （DTs） are established in terms of the diverse feature sets. And then the uncertainty measures of the separability are induced, in the form of mass functions in Dempster-Shafer theory （DST）, from each DTs based on generalized rough set model. From the mass functions, all the weights are calculated by a modified heuristic fusion function and assigned dynamically to each classifier varying with its output. The comparison experiment is performed on the hyperspectral remote sensing images. And the experimental results show that the performance of the classification can be improved by using the proposed method compared with the plurality voting （PV）.展开更多
In order to enhance the quality of vertical handoff in an overlay wireless network, multiple attributes are taken into account when optimizing the vertical handoff decision including user-based and network-based QoS f...In order to enhance the quality of vertical handoff in an overlay wireless network, multiple attributes are taken into account when optimizing the vertical handoff decision including user-based and network-based QoS factors. In this paper, we develop a novel vertical handoff algorithm in an integrated 3G cellular and Wireless LAN networks. The proposed algorithm can adjust the weight of each QoS attribute dynamically as the networks change, trace the network condition and choose the optimal access point at transient regions. Simulation results show that this algorithm is able to provide accurate handoff decision, resulting in small unnecessary handoff numbers, good performance of throughput and handoff delay in heterogeneous environments.展开更多
A dynamic weight function method is presented for dynamic stress intensity factors of circular disk with a radial edge crack under external impulsive pressure. The dynamic stresses in a circular disk are solved under ...A dynamic weight function method is presented for dynamic stress intensity factors of circular disk with a radial edge crack under external impulsive pressure. The dynamic stresses in a circular disk are solved under abrupt step external pressure using the eigenfunction method. The solution consists of a quasi-static solution satisfying inhomogeneous boundary conditions and a dynamic solution satisfying homogeneous boundary conditions. By making use of Fourier- Bessel series expansion, the history and distribution of dynamic stresses in the circular disk are derived. Furthermore, the equation for stress intensity factors under uniform pressure is used as the reference case, the weight function equation for the circular disk containing an edge crack is worked out, and the dynamic stress intensity factor equation for the circular disk containing a radial edge crack can be given. The results indicate that the stress intensity factors under sudden step external pressure vary periodically with time, and the ratio of the maximum value of dynamic stress intensity factors to the corresponding static value is about 2.0.展开更多
The random forest model is universal and easy to understand, which is often used for classification and prediction. However, it uses non-selective integration and the majority rule to judge the final result, thus the ...The random forest model is universal and easy to understand, which is often used for classification and prediction. However, it uses non-selective integration and the majority rule to judge the final result, thus the difference between the decision trees in the model is ignored and the prediction accuracy of the model is reduced. Taking into consideration these defects, an improved random forest model based on confusion matrix (CM-RF)is proposed. The decision tree cluster is selectively constructed by the similarity measure in the process of constructing the model, and the result is output by using the dynamic weighted voting fusion method in the final voting session. Experiments show that the proposed CM-RF can reduce the impact of low-performance decision trees on the output result, thus improving the accuracy and generalization ability of random forest model.展开更多
Dynamic stress intensity factors are evaluated for thick-walled cylinder with a radial edge crack under internal impulsive pressure. Firstly, the equation for stress intensity factors under static uniform pressure is ...Dynamic stress intensity factors are evaluated for thick-walled cylinder with a radial edge crack under internal impulsive pressure. Firstly, the equation for stress intensity factors under static uniform pressure is used as the reference case, and then the weight function for a thick-walled cylinder containing a radial edge crack can be worked out. Secondly, the dynamic stresses in uncracked thick-walled cylinders are solved under internal impulsive pressure by using mode shape function method. The solution consists of a quasi-static solution satisfying inhomogeneous boundary conditions and a dynamic solution satisfying homogeneous boundary condi- tions, and the history and distribution of dynamic stresses in thick-walled cylinders are derived in terms of Fourier-Bessel series. Finally, the dynamic stress intensity factor equations for thick-walled cylinder containing a radial edge crack sub- jected to internal impulsive pressure are given by dynamic weight function method. The finite element method is utilized to verify the results of numerical examples, showing the validity and feasibility of the proposed method.展开更多
Through analysis of operational evaluation factors for tide forecasting, the relationship between the evaluation factors and the weights of forecasters was examined. A tide forecasting method based on dynamic weight d...Through analysis of operational evaluation factors for tide forecasting, the relationship between the evaluation factors and the weights of forecasters was examined. A tide forecasting method based on dynamic weight distribution for operational evaluation was developed, and multiple-forecaster synchronous forecasting was realized while avoiding the instability cased by only one forecaster. Weights were distributed to the forecasters according to each one＇s forecast precision. An evaluation criterion for the professional level of the forecasters was also built. The eligibility rates of forecast results demonstrate the skill of the forecasters and the stability of their forecasts. With the developed tide forecasting method, the precision and reasonableness of tide forecasting are improved. The application of the present method to tide forecasting at the Huangpu Park tidal station demonstrates the validity of the method.展开更多
A novel scheme to construct a hash function based on a weighted complex dynamical network （WCDN） generated from an original message is proposed in this paper. First, the original message is divided into blocks. Then...A novel scheme to construct a hash function based on a weighted complex dynamical network （WCDN） generated from an original message is proposed in this paper. First, the original message is divided into blocks. Then, each block is divided into components, and the nodes and weighted edges are well defined from these components and their relations. Namely, the WCDN closely related to the original message is established. Furthermore, the node dynamics of the WCDN are chosen as a chaotic map. After chaotic iterations, quantization and exclusive-or operations, the fixed-length hash value is obtained. This scheme has the property that any tiny change in message can be diffused rapidly through the WCDN, leading to very different hash values. Analysis and simulation show that the scheme possesses good statistical properties, excellent confusion and diffusion, strong collision resistance and high efficiency.展开更多
Summary： The purpose of this study was to quantitatively analyze the relationship between three di- mensional arterial spin labeling （3D-ASL） and dynamic susceptibility contrast-enhanced perfusion weighted imaging ...Summary： The purpose of this study was to quantitatively analyze the relationship between three di- mensional arterial spin labeling （3D-ASL） and dynamic susceptibility contrast-enhanced perfusion weighted imaging （DSC-PWI） in ischemic stroke patients. Thirty patients with ischemic stroke were in- cluded in this study. All subjects underwent routine magnetic resonance imaging scanning, diffusion weighted imaging （DWI）, magnetic resonance angiography （MRA）, 3D-ASL and DSC-PWI on a 3.0T MR scanner. Regions of interest （ROIs） were drawn on the cerebral blood flow （CBF） maps （derived from ASL） and multi-parametric DSC perfusion maps, and then, the absolute and relative values of ASL-CBF, DSC-derived CBF, and DSC-derived mean transit time （MTT） were calculated. The rela- tionships between ASL and DSC parameters were analyzed using Pearson＇s correlation analysis. Re- ceiver operative characteristic （ROC） curves were performed to define the thresholds of relative value of ASL-CBF （rASL） that could best predict DSC-CBF reduction and MTT prolongation. Relative ASL better correlated with CBF and MTT in the anterior circulation with the Pearson correlation coefficients （R） values being 0.611 （P〈0.001） and-0.610 （P〈0.001） respectively. ROC curves demonstrated that when rASL 〈0.585, the sensitivity, specificity and accuracy for predicting ROIs with rCBF〈0.9 were 92.3%, 63.6% and 76.6% respectively. When rASL 〈0.952, the sensitivity, specificity and accuracy for predicting ROIs rMTT〉I.0 were 75.7%, 89.2% and 87.8% respectively. ASL-CBF map has better linear correlations with DSC-derived parameters （DSC-CBF and MTT） in anterior circulation in ischemic stroke patients. Additionally, when rASL is lower than 0.585, it could predict DSC-CBF decrease with moderate accuracy. IfrASL values range from 0.585 to 0.952, we just speculate the prolonged MTT.展开更多
This paper firstly introduced the degree of livability of a city from the social civilization,economic affluence,environmental beauty,resource carrying capacity,and life convenience. Based on the principle of the fuzz...This paper firstly introduced the degree of livability of a city from the social civilization,economic affluence,environmental beauty,resource carrying capacity,and life convenience. Based on the principle of the fuzzy comprehensive evaluation,it analyzed the connection between influencing factors,and established a comprehensive evaluation model for calculation of the livability index of a city. Finally,it obtained the relative livability of each city and the ranking of livability of each city.展开更多
Static strength finite element analysis was conducted to decrease the weight of a skeleton vehicle＇s frame. Results indicated that the maximum stress occurs on the front beam ＇s variable section area. Dynamic sensit...Static strength finite element analysis was conducted to decrease the weight of a skeleton vehicle＇s frame. Results indicated that the maximum stress occurs on the front beam ＇s variable section area. Dynamic sensitivity analysis elucidated the relationship between the maximum stress and the thickness of a particular beam,e. g.,top,middle,and bottom beam. Displacement was analyzed by the key part that influenced the maximum stress. Finally,the new plan using BS960 super-high-strength beam steel and the preferred beam thickness was compared with the original plan. New combinations of beam thickness were introduced on the basis of different purposes; the maximum responding light w eight ratio was 21%.展开更多
Automatic gauge control(AGC in the article)is the key technology of product thickness accuracy and flatness quality in modern cold rolling mill.Most traditional AGC control algorithms need stable external system condi...Automatic gauge control(AGC in the article)is the key technology of product thickness accuracy and flatness quality in modern cold rolling mill.Most traditional AGC control algorithms need stable external system conditions and hard to stabilize under complex interference that meets coverage requirements.This paper presents a new anti-interference strategy for AGC control of 20-Hi cold reversing mill.The proposed algorithm introduces a united dynamic weights algorithm of feed forward-mass flow to avoid the complex interference problem in AGC control,the relevant control strategy is provided to eliminate the adverse effects.At the same time,the D-value between feed forward-mass flow pre-computation and thickness measurement deviation is dynamic compared,the final gap position regulation is calculated by developing a set of united dynamic weights between feed forward control and mass flow control.Finally,the output of controllers is sent to actuator though a constant rate smoothing.The proposed strategy is compared with conventional AGC control on Experimental platform and project application,the results show that the proposed strategy is more stable than comparison method and majority of system uncertainty produced by mentioned interference is significantly eliminated.展开更多
Nowadays,optimization techniques are required in various engineering domains to find optimal solutions for complex problems.As a result,there is a growing tendency among scientists to enhance existing nature-inspired ...Nowadays,optimization techniques are required in various engineering domains to find optimal solutions for complex problems.As a result,there is a growing tendency among scientists to enhance existing nature-inspired algorithms using various evolutionary strategies and to develop new nature-inspired optimization methods that can properly explore the feature space.The recently designed nature-inspired meta-heuristic,named the Golden Jackal Optimization(GJO),was inspired by the collaborative hunting actions of the golden jackal in nature to solve various challenging problems.However,like other approaches,the GJO has the limitations of poor exploitation ability,the ease of getting stuck in a local optimal region,and an improper balancing of exploration and exploitation.To overcome these limitations,this paper proposes an improved GJO algorithm based on multi-strategy mixing(LGJO).First,using a chaotic mapping strategy to initialize the population instead of using random parameters,this algorithm can generate initial solutions with good diversity in the search space.Second,a dynamic inertia weight based on cosine variation is proposed to make the search process more realistic and effectively balance the algorithm's global and local search capabilities.Finally,a position update strategy based on Gaussian mutation was introduced,fully utilizing the guidance role of the optimal individual to improve population diversity,effectively exploring unknown regions,and avoiding the algorithm falling into local optima.To evaluate the proposed algorithm,23 mathematical benchmark functions,CEC-2019 and CEC2021 tests are employed.The results are compared to high-quality,well-known optimization methods.The results of the proposed method are compared from different points of view,including the quality of the results,convergence behavior,and robustness.The superiority and high-quality performance of the proposed method are demonstrated by comparing the results.Furthermore,to demonstrate its applicability,it is employed to solve four constrained industrial applications.The outcomes of the experiment reveal that the proposed algorithm can solve challenging,constrained problems and is very competitive compared with other optimization algorithms.This article provides a new approach to solving real-world optimization problems.展开更多
In this paper, the theory of constructing optimal dynamical systems based on weighted residual presented by Wu & Sha is applied to three-dimensional Navier-Stokes equations, and the optimal dynamical system modeli...In this paper, the theory of constructing optimal dynamical systems based on weighted residual presented by Wu & Sha is applied to three-dimensional Navier-Stokes equations, and the optimal dynamical system modeling equations are derived. Then the multiscale global optimization method based on coarse graining analysis is presented, by which a set of approximate global optimal bases is directly obtained from Navier-Stokes equations and the construction of optimal dynamical systems is realized. The optimal bases show good properties, such as showing the physical properties of complex flows and the turbulent vortex structures, being intrinsic to real physical problem and dynamical systems, and having scaling symmetry in mathematics, etc.. In conclusion, using fewer terms of optimal bases will approach the exact solutions of Navier-Stokes equations, and the dynamical systems based on them show the most optimal behavior.展开更多
Automatic segmentation and classification of brain tumors are of great importance to clinical treatment.However,they are challenging due to the varied and small morphology of the tumors.In this paper,we propose a mult...Automatic segmentation and classification of brain tumors are of great importance to clinical treatment.However,they are challenging due to the varied and small morphology of the tumors.In this paper,we propose a multitask multiscale residual attention network(MMRAN)to simultaneously solve the problem of accurately segmenting and classifying brain tumors.The proposed MMRAN is based on U-Net,and a parallel branch is added at the end of the encoder as the classification network.First,we propose a novel multiscale residual attention module(MRAM)that can aggregate contextual features and combine channel attention and spatial attention better and add it to the shared parameter layer of MMRAN.Second,we propose a method of dynamic weight training that can improve model performance while minimizing the need for multiple experiments to determine the optimal weights for each task.Finally,prior knowledge of brain tumors is added to the postprocessing of segmented images to further improve the segmentation accuracy.We evaluated MMRAN on a brain tumor data set containing meningioma,glioma,and pituitary tumors.In terms of segmentation performance,our method achieves Dice,Hausdorff distance(HD),mean intersection over union(MIoU),and mean pixel accuracy(MPA)values of 80.03%,6.649 mm,84.38%,and 89.41%,respectively.In terms of classification performance,our method achieves accuracy,recall,precision,and F1-score of 89.87%,90.44%,88.56%,and 89.49%,respectively.Compared with other networks,MMRAN performs better in segmentation and classification,which significantly aids medical professionals in brain tumor management.The code and data set are available at https://github.com/linkenfaqiu/MMRAN.展开更多
Being a new-generation C4ISR system simulation method,the construction approach of net-centric simulation(NCS)is developing toward net-centric from the traditional approach of platform-centric.NCS is mainly completed ...Being a new-generation C4ISR system simulation method,the construction approach of net-centric simulation(NCS)is developing toward net-centric from the traditional approach of platform-centric.NCS is mainly completed by the construction of the simulation task community(STC),the key to which being the dynamic integration of the various services spread in the network in order to form a new STC that meets the requirements of different users.In this study,a simulation task community service selection algorithm(STCSSA)is proposed.The main idea of this algorithm is to transform the construction of STC to the searching of optimal multi-objectives services with QoS global constraints.This paper first introduces the QoS model of STC and evaluates the service composition process,then presents the detailed operating process of STCSSA and design of the dynamic inertia weight strategy of the algorithm,and also proposes an optional variation method.Comparative tests were performed on STCSSA with other particle swarm optimization algorithms.It was validated from the perspective of performance that the proposed algorithm has advantages in improving the rate of convergence and avoiding local optimum,and from the perspective of practical application STCSSA also demonstrated feasibility in the construction of large-scale NCS task community.展开更多
文摘The evolutionary strategy with a dynamic weighting schedule is proposed to find all the compromised solutions of the multi-objective integrated structure and control optimization problem, where the optimal system performance and control cost are defined by H2 or H∞ norms. During this optimization process, the weights are varying with the increasing generation instead of fixed values. The proposed strategy together with the linear matrix inequality （LMI） or the Riccati controller design method can find a series of uniformly distributed nondominated solutions in a single run. Therefore, this method can greatly reduce the computation intensity of the integrated optimization problem compared with the weight-based single objective genetic algorithm. Active automotive suspension is adopted as an example to illustrate the effectiveness of the proposed method.
基金Innovation and Development Project of China Meteorological Administration(CXFZ2023J044)Innovation Foundation of CMA Public Meteorological Service Center(K2023002)+1 种基金“Tianchi Talents”Introduction Plan(2023)Key Innovation Team for Energy and Meteorology of China Meteorological Administration。
文摘In the present study,multimodel ensemble forecast experiments of the global horizontal irradiance(GHI)were conducted using the dynamic variable weight technique.The study was based on the forecasts of four numerical models,namely,the China Meteorological Administration Wind Energy and Solar Energy Prediction System,the Mesoscale Weather Numerical Prediction System of China Meteorological Administration,the China Meteorological Administration Regional Mesoscale Numerical Prediction System-Guangdong,and the Weather Research and Forecasting Model-Solar,and observational data from four photovoltaic(PV)power stations in Yangjiang City,Guangdong Province.The results show that compared with those of the monthly optimal numerical model forecasts,the dynamic variable weight-based ensemble forecasts exhibited 0.97%-15.96%smaller values of the mean absolute error and 3.31%-18.40%lower values of the root mean square error(RMSE).However,the increase in the correlation coefficient was not obvious.Specifically,the multimodel ensemble mainly improved the performance of GHI forecasts below 700 W m^(-2),particularly below 400 W m^(-2),with RMSE reductions as high as 7.56%-28.28%.In contrast,the RMSE increased at GHI levels above 700 W m^(-2).As for the key period of PV power station output(02:00-07:00),the accuracy of GHI forecasts could be improved by the multimodel ensemble:the multimodel ensemble could effectively decrease the daily maximum absolute error(AE max)of GHI forecasts.Moreover,with increasing forecasting difficulty under cloudy conditions,the multimodel ensemble,which yields data closer to the actual observations,could simulate GHI fluctuations more accurately.
基金the National Natural Science Foundation of China(No.72073041)Open Foundation for the University Innovation Platform in Hunan Province(No.18K103)+2 种基金2011 Collaborative Innovation Center for Development and Utilization of Finance and Economics Big Data Property,Universities of Hunan Province,Open Project(Nos.20181901CRP03,20181901CRP04,20181901CRP05)2020 Hunan Provincial Higher Education Teaching Reform Research Project(Nos.HNJG-2020-1130,HNJG-2020-1124)2020 General Project of Hunan Social Science Fund(No.20B16).
文摘Using the RFM(Recency,Frequency,Monetary value)model can provide valuable insights about customer clusterswhich is the core of customer relationship management.Due to accurate customer segment coming from dynamic weighted applications,in-depth targeted marketing may also use type of dynamic weight of R,F and M as factors.In this paper,we present our dynamic weighted RFM approach which is intended to improve the performance of customer segmentation by using the factors and variations to attain dynamic weights.Our dynamic weight approach is a kind of Custom method in essential which roots in the understanding of the data set.Firstly,Analytic Hierarchy Process is used to calculate the subjective weight,then the entropy method is applied to calculate the objective weight.Finally,we use comprehensive integration weighting method to combine the subjective and objective weight to obtain the final weight of the index to calculate the individual user value and quantify the user value difference.The experiment shows that the dynamic weight we used in RFM model is vital,affects the customer segmentation performance positively.Also,this study indicates that customer segments containing dynamic weighted RFM scores bring about stronger and more accurate association rules for the understanding of customer behavior.At last,we discuss the limitations of RFM analysis.
基金This project was supported by the National Basic Research Programof China (2001CB309403)
文摘To improve the performance of multiple classifier system, a knowledge discovery based dynamic weighted voting （KD-DWV） is proposed based on knowledge discovery. In the method, all base classifiers may be allowed to operate in different measurement/feature spaces to make the most of diverse classification information. The weights assigned to each output of a base classifier are estimated by the separability of training sample sets in relevant feature space. For this purpose, some decision tables （DTs） are established in terms of the diverse feature sets. And then the uncertainty measures of the separability are induced, in the form of mass functions in Dempster-Shafer theory （DST）, from each DTs based on generalized rough set model. From the mass functions, all the weights are calculated by a modified heuristic fusion function and assigned dynamically to each classifier varying with its output. The comparison experiment is performed on the hyperspectral remote sensing images. And the experimental results show that the performance of the classification can be improved by using the proposed method compared with the plurality voting （PV）.
基金Acknowledgements This work is supported by Key Program of National Natural Science Foundation of China Grant No. 60832009.
文摘In order to enhance the quality of vertical handoff in an overlay wireless network, multiple attributes are taken into account when optimizing the vertical handoff decision including user-based and network-based QoS factors. In this paper, we develop a novel vertical handoff algorithm in an integrated 3G cellular and Wireless LAN networks. The proposed algorithm can adjust the weight of each QoS attribute dynamically as the networks change, trace the network condition and choose the optimal access point at transient regions. Simulation results show that this algorithm is able to provide accurate handoff decision, resulting in small unnecessary handoff numbers, good performance of throughput and handoff delay in heterogeneous environments.
文摘A dynamic weight function method is presented for dynamic stress intensity factors of circular disk with a radial edge crack under external impulsive pressure. The dynamic stresses in a circular disk are solved under abrupt step external pressure using the eigenfunction method. The solution consists of a quasi-static solution satisfying inhomogeneous boundary conditions and a dynamic solution satisfying homogeneous boundary conditions. By making use of Fourier- Bessel series expansion, the history and distribution of dynamic stresses in the circular disk are derived. Furthermore, the equation for stress intensity factors under uniform pressure is used as the reference case, the weight function equation for the circular disk containing an edge crack is worked out, and the dynamic stress intensity factor equation for the circular disk containing a radial edge crack can be given. The results indicate that the stress intensity factors under sudden step external pressure vary periodically with time, and the ratio of the maximum value of dynamic stress intensity factors to the corresponding static value is about 2.0.
基金Science Research Project of Gansu Provincial Transportation Department(No.2017-012)
文摘The random forest model is universal and easy to understand, which is often used for classification and prediction. However, it uses non-selective integration and the majority rule to judge the final result, thus the difference between the decision trees in the model is ignored and the prediction accuracy of the model is reduced. Taking into consideration these defects, an improved random forest model based on confusion matrix (CM-RF)is proposed. The decision tree cluster is selectively constructed by the similarity measure in the process of constructing the model, and the result is output by using the dynamic weighted voting fusion method in the final voting session. Experiments show that the proposed CM-RF can reduce the impact of low-performance decision trees on the output result, thus improving the accuracy and generalization ability of random forest model.
基金supported by the China Aviation Industry Corporation I Program (ATPD-1104-02).
文摘Dynamic stress intensity factors are evaluated for thick-walled cylinder with a radial edge crack under internal impulsive pressure. Firstly, the equation for stress intensity factors under static uniform pressure is used as the reference case, and then the weight function for a thick-walled cylinder containing a radial edge crack can be worked out. Secondly, the dynamic stresses in uncracked thick-walled cylinders are solved under internal impulsive pressure by using mode shape function method. The solution consists of a quasi-static solution satisfying inhomogeneous boundary conditions and a dynamic solution satisfying homogeneous boundary condi- tions, and the history and distribution of dynamic stresses in thick-walled cylinders are derived in terms of Fourier-Bessel series. Finally, the dynamic stress intensity factor equations for thick-walled cylinder containing a radial edge crack sub- jected to internal impulsive pressure are given by dynamic weight function method. The finite element method is utilized to verify the results of numerical examples, showing the validity and feasibility of the proposed method.
文摘Through analysis of operational evaluation factors for tide forecasting, the relationship between the evaluation factors and the weights of forecasters was examined. A tide forecasting method based on dynamic weight distribution for operational evaluation was developed, and multiple-forecaster synchronous forecasting was realized while avoiding the instability cased by only one forecaster. Weights were distributed to the forecasters according to each one＇s forecast precision. An evaluation criterion for the professional level of the forecasters was also built. The eligibility rates of forecast results demonstrate the skill of the forecasters and the stability of their forecasts. With the developed tide forecasting method, the precision and reasonableness of tide forecasting are improved. The application of the present method to tide forecasting at the Huangpu Park tidal station demonstrates the validity of the method.
基金Project supported by the Natural Science Foundation of Jiangsu Province, China (Grant No. BK2010526)the Specialized Research Fund for the Doctoral Program of Higher Education of China (Grant No. 20103223110003)The Ministry of Education Research in the Humanities and Social Sciences Planning Fund, China (Grant No. 12YJAZH120)
文摘A novel scheme to construct a hash function based on a weighted complex dynamical network （WCDN） generated from an original message is proposed in this paper. First, the original message is divided into blocks. Then, each block is divided into components, and the nodes and weighted edges are well defined from these components and their relations. Namely, the WCDN closely related to the original message is established. Furthermore, the node dynamics of the WCDN are chosen as a chaotic map. After chaotic iterations, quantization and exclusive-or operations, the fixed-length hash value is obtained. This scheme has the property that any tiny change in message can be diffused rapidly through the WCDN, leading to very different hash values. Analysis and simulation show that the scheme possesses good statistical properties, excellent confusion and diffusion, strong collision resistance and high efficiency.
基金supported by grants from the 12th Five-year Science and Technology Support Program of China(No.2011BAI08B10)the National Natural Science Foundation of China(No.81171308,No.81570462)
文摘Summary： The purpose of this study was to quantitatively analyze the relationship between three di- mensional arterial spin labeling （3D-ASL） and dynamic susceptibility contrast-enhanced perfusion weighted imaging （DSC-PWI） in ischemic stroke patients. Thirty patients with ischemic stroke were in- cluded in this study. All subjects underwent routine magnetic resonance imaging scanning, diffusion weighted imaging （DWI）, magnetic resonance angiography （MRA）, 3D-ASL and DSC-PWI on a 3.0T MR scanner. Regions of interest （ROIs） were drawn on the cerebral blood flow （CBF） maps （derived from ASL） and multi-parametric DSC perfusion maps, and then, the absolute and relative values of ASL-CBF, DSC-derived CBF, and DSC-derived mean transit time （MTT） were calculated. The rela- tionships between ASL and DSC parameters were analyzed using Pearson＇s correlation analysis. Re- ceiver operative characteristic （ROC） curves were performed to define the thresholds of relative value of ASL-CBF （rASL） that could best predict DSC-CBF reduction and MTT prolongation. Relative ASL better correlated with CBF and MTT in the anterior circulation with the Pearson correlation coefficients （R） values being 0.611 （P〈0.001） and-0.610 （P〈0.001） respectively. ROC curves demonstrated that when rASL 〈0.585, the sensitivity, specificity and accuracy for predicting ROIs with rCBF〈0.9 were 92.3%, 63.6% and 76.6% respectively. When rASL 〈0.952, the sensitivity, specificity and accuracy for predicting ROIs rMTT〉I.0 were 75.7%, 89.2% and 87.8% respectively. ASL-CBF map has better linear correlations with DSC-derived parameters （DSC-CBF and MTT） in anterior circulation in ischemic stroke patients. Additionally, when rASL is lower than 0.585, it could predict DSC-CBF decrease with moderate accuracy. IfrASL values range from 0.585 to 0.952, we just speculate the prolonged MTT.
文摘This paper firstly introduced the degree of livability of a city from the social civilization,economic affluence,environmental beauty,resource carrying capacity,and life convenience. Based on the principle of the fuzzy comprehensive evaluation,it analyzed the connection between influencing factors,and established a comprehensive evaluation model for calculation of the livability index of a city. Finally,it obtained the relative livability of each city and the ranking of livability of each city.
文摘Static strength finite element analysis was conducted to decrease the weight of a skeleton vehicle＇s frame. Results indicated that the maximum stress occurs on the front beam ＇s variable section area. Dynamic sensitivity analysis elucidated the relationship between the maximum stress and the thickness of a particular beam,e. g.,top,middle,and bottom beam. Displacement was analyzed by the key part that influenced the maximum stress. Finally,the new plan using BS960 super-high-strength beam steel and the preferred beam thickness was compared with the original plan. New combinations of beam thickness were introduced on the basis of different purposes; the maximum responding light w eight ratio was 21%.
文摘Automatic gauge control(AGC in the article)is the key technology of product thickness accuracy and flatness quality in modern cold rolling mill.Most traditional AGC control algorithms need stable external system conditions and hard to stabilize under complex interference that meets coverage requirements.This paper presents a new anti-interference strategy for AGC control of 20-Hi cold reversing mill.The proposed algorithm introduces a united dynamic weights algorithm of feed forward-mass flow to avoid the complex interference problem in AGC control,the relevant control strategy is provided to eliminate the adverse effects.At the same time,the D-value between feed forward-mass flow pre-computation and thickness measurement deviation is dynamic compared,the final gap position regulation is calculated by developing a set of united dynamic weights between feed forward control and mass flow control.Finally,the output of controllers is sent to actuator though a constant rate smoothing.The proposed strategy is compared with conventional AGC control on Experimental platform and project application,the results show that the proposed strategy is more stable than comparison method and majority of system uncertainty produced by mentioned interference is significantly eliminated.
基金support of the special project for collaborative innovation of science and technology in 2021(No:202121206)Henan Province University Scientific and Technological Innovation Team(No:18IRTSTHN009).
文摘Nowadays,optimization techniques are required in various engineering domains to find optimal solutions for complex problems.As a result,there is a growing tendency among scientists to enhance existing nature-inspired algorithms using various evolutionary strategies and to develop new nature-inspired optimization methods that can properly explore the feature space.The recently designed nature-inspired meta-heuristic,named the Golden Jackal Optimization(GJO),was inspired by the collaborative hunting actions of the golden jackal in nature to solve various challenging problems.However,like other approaches,the GJO has the limitations of poor exploitation ability,the ease of getting stuck in a local optimal region,and an improper balancing of exploration and exploitation.To overcome these limitations,this paper proposes an improved GJO algorithm based on multi-strategy mixing(LGJO).First,using a chaotic mapping strategy to initialize the population instead of using random parameters,this algorithm can generate initial solutions with good diversity in the search space.Second,a dynamic inertia weight based on cosine variation is proposed to make the search process more realistic and effectively balance the algorithm's global and local search capabilities.Finally,a position update strategy based on Gaussian mutation was introduced,fully utilizing the guidance role of the optimal individual to improve population diversity,effectively exploring unknown regions,and avoiding the algorithm falling into local optima.To evaluate the proposed algorithm,23 mathematical benchmark functions,CEC-2019 and CEC2021 tests are employed.The results are compared to high-quality,well-known optimization methods.The results of the proposed method are compared from different points of view,including the quality of the results,convergence behavior,and robustness.The superiority and high-quality performance of the proposed method are demonstrated by comparing the results.Furthermore,to demonstrate its applicability,it is employed to solve four constrained industrial applications.The outcomes of the experiment reveal that the proposed algorithm can solve challenging,constrained problems and is very competitive compared with other optimization algorithms.This article provides a new approach to solving real-world optimization problems.
基金supported by the National Natural Science Foundation of China(Grant Nos.11372068 and 11572350)the National Basic Research Program of China(Grant No.2014CB744104)
文摘In this paper, the theory of constructing optimal dynamical systems based on weighted residual presented by Wu & Sha is applied to three-dimensional Navier-Stokes equations, and the optimal dynamical system modeling equations are derived. Then the multiscale global optimization method based on coarse graining analysis is presented, by which a set of approximate global optimal bases is directly obtained from Navier-Stokes equations and the construction of optimal dynamical systems is realized. The optimal bases show good properties, such as showing the physical properties of complex flows and the turbulent vortex structures, being intrinsic to real physical problem and dynamical systems, and having scaling symmetry in mathematics, etc.. In conclusion, using fewer terms of optimal bases will approach the exact solutions of Navier-Stokes equations, and the dynamical systems based on them show the most optimal behavior.
基金This paper was supported by National Natural Science Foundation of China(No.61977063 and 61872020).The authors thank all the patients for providing their MRI images and School of Biomedical Engineering at Southern Medical University,China for providing the brain tumor data set.We appreciate Dr.Fenfen Li,Wenzhou Eye Hospital,Wenzhou Medical University,China,for her support with clinical consulting and language editing.
文摘Automatic segmentation and classification of brain tumors are of great importance to clinical treatment.However,they are challenging due to the varied and small morphology of the tumors.In this paper,we propose a multitask multiscale residual attention network(MMRAN)to simultaneously solve the problem of accurately segmenting and classifying brain tumors.The proposed MMRAN is based on U-Net,and a parallel branch is added at the end of the encoder as the classification network.First,we propose a novel multiscale residual attention module(MRAM)that can aggregate contextual features and combine channel attention and spatial attention better and add it to the shared parameter layer of MMRAN.Second,we propose a method of dynamic weight training that can improve model performance while minimizing the need for multiple experiments to determine the optimal weights for each task.Finally,prior knowledge of brain tumors is added to the postprocessing of segmented images to further improve the segmentation accuracy.We evaluated MMRAN on a brain tumor data set containing meningioma,glioma,and pituitary tumors.In terms of segmentation performance,our method achieves Dice,Hausdorff distance(HD),mean intersection over union(MIoU),and mean pixel accuracy(MPA)values of 80.03%,6.649 mm,84.38%,and 89.41%,respectively.In terms of classification performance,our method achieves accuracy,recall,precision,and F1-score of 89.87%,90.44%,88.56%,and 89.49%,respectively.Compared with other networks,MMRAN performs better in segmentation and classification,which significantly aids medical professionals in brain tumor management.The code and data set are available at https://github.com/linkenfaqiu/MMRAN.
基金supported by the following funds and projects:the National Defense Key 973 Projectthe State Key Laboratory Fundthe China Electronics Technology Group Corporation Fund。
文摘Being a new-generation C4ISR system simulation method,the construction approach of net-centric simulation(NCS)is developing toward net-centric from the traditional approach of platform-centric.NCS is mainly completed by the construction of the simulation task community(STC),the key to which being the dynamic integration of the various services spread in the network in order to form a new STC that meets the requirements of different users.In this study,a simulation task community service selection algorithm(STCSSA)is proposed.The main idea of this algorithm is to transform the construction of STC to the searching of optimal multi-objectives services with QoS global constraints.This paper first introduces the QoS model of STC and evaluates the service composition process,then presents the detailed operating process of STCSSA and design of the dynamic inertia weight strategy of the algorithm,and also proposes an optional variation method.Comparative tests were performed on STCSSA with other particle swarm optimization algorithms.It was validated from the perspective of performance that the proposed algorithm has advantages in improving the rate of convergence and avoiding local optimum,and from the perspective of practical application STCSSA also demonstrated feasibility in the construction of large-scale NCS task community.
