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Interval grey number sequence prediction by using non-homogenous exponential discrete grey forecasting model 被引量:19
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作者 Naiming Xie Sifeng Liu 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2015年第1期96-102,共7页
This paper aims to study a new grey prediction approach and its solution for forecasting the main system variable whose accurate value could not be collected while the potential value set could be defined. Based on th... This paper aims to study a new grey prediction approach and its solution for forecasting the main system variable whose accurate value could not be collected while the potential value set could be defined. Based on the traditional nonhomogenous discrete grey forecasting model(NDGM), the interval grey number and its algebra operations are redefined and combined with the NDGM model to construct a new interval grey number sequence prediction approach. The solving principle of the model is analyzed, the new accuracy evaluation indices, i.e. mean absolute percentage error of mean value sequence(MAPEM) and mean percent of interval sequence simulating value set covered(MPSVSC), are defined and, the procedure of the interval grey number sequence based the NDGM(IG-NDGM) is given out. Finally, a numerical case is used to test the modelling accuracy of the proposed model. Results show that the proposed approach could solve the interval grey number sequence prediction problem and it is much better than the traditional DGM(1,1) model and GM(1,1) model. 展开更多
关键词 grey number grey system theory INTERVAL discrete grey forecasting model non-homogeneous exponential sequence
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A new grey forecasting model based on BP neural network and Markov chain 被引量:6
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作者 李存斌 王恪铖 《Journal of Central South University of Technology》 EI 2007年第5期713-718,共6页
A new grey forecasting model based on BP neural network and Markov chain was proposed. In order to combine the grey forecasting model with neural network, an important theorem that the grey differential equation is eq... A new grey forecasting model based on BP neural network and Markov chain was proposed. In order to combine the grey forecasting model with neural network, an important theorem that the grey differential equation is equivalent to the time response model, was proved by analyzing the features of grey forecasting model(GM(1,1)). Based on this, the differential equation parameters were included in the network when the BP neural network was constructed, and the neural network was trained by extracting samples from grey system's known data. When BP network was converged, the whitened grey differential equation parameters were extracted and then the grey neural network forecasting model (GNNM(1,1)) was built. In order to reduce stochastic phenomenon in GNNM(1,1), the state transition probability between two states was defined and the Markov transition matrix was established by building the residual sequences between grey forecasting and actual value. Thus, the new grey forecasting model(MNNGM(1,1)) was proposed by combining Markov chain with GNNM(1,1). Based on the above discussion, three different approaches were put forward for forecasting China electricity demands. By comparing GM(1, 1) and GNNM(1,1) with the proposed model, the results indicate that the absolute mean error of MNNGM(1,1) is about 0.4 times of GNNM(1,1) and 0.2 times of GM(I, 1), and the mean square error of MNNGM(1,1) is about 0.25 times of GNNM(1,1) and 0.1 times of GM(1,1). 展开更多
关键词 grey forecasting model neural network Markov chain electricity demand forecasting
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A self-adaptive grey forecasting model and its application
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作者 TANG Xiaozhong XIE Naiming 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2022年第3期665-673,共9页
GM(1,1)models have been widely used in various fields due to their high performance in time series prediction.However,some hypotheses of the existing GM(1,1)model family may reduce their prediction performance in some... GM(1,1)models have been widely used in various fields due to their high performance in time series prediction.However,some hypotheses of the existing GM(1,1)model family may reduce their prediction performance in some cases.To solve this problem,this paper proposes a self-adaptive GM(1,1)model,termed as SAGM(1,1)model,which aims to solve the defects of the existing GM(1,1)model family by deleting their modeling hypothesis.Moreover,a novel multi-parameter simultaneous optimization scheme based on firefly algorithm is proposed,the proposed multi-parameter optimization scheme adopts machine learning ideas,takes all adjustable parameters of SAGM(1,1)model as input variables,and trains it with firefly algorithm.And Sobol’sensitivity indices are applied to study global sensitivity of SAGM(1,1)model parameters,which provides an important reference for model parameter calibration.Finally,forecasting capability of SAGM(1,1)model is illustrated by Anhui electricity consumption dataset.Results show that prediction accuracy of SAGM(1,1)model is significantly better than other models,and it is shown that the proposed approach enhances the prediction performance of GM(1,1)model significantly. 展开更多
关键词 grey forecasting model GM(1 1)model firefly algo-rithm Sobol’sensitivity indices electricity consumption prediction
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Grey relationship analysis and grey forecasting modeling on thermal stability of synthetic single diamond
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作者 王适 张弘弢 董海 《Journal of Harbin Institute of Technology(New Series)》 EI CAS 2006年第1期73-78,共6页
Through analyzing 7 Ib-type samples of synthetic single diamonds by their DTA and TG in air, we ascertained the extrapolated onset temperature on the curves of DTA as the characteristic temperature of their thermal st... Through analyzing 7 Ib-type samples of synthetic single diamonds by their DTA and TG in air, we ascertained the extrapolated onset temperature on the curves of DTA as the characteristic temperature of their thermal stabilities. Based on the grey system theory, we analyzed 4 factors influential in the thermal stability by the grey relationship analysis, a quantitative method, and derived the grey relationship sequence, that is, the rank of the influence extent of 4 factors on the thermal stability. Furthermore, we established the grey forecasting model, namely GM(1,5), for predicting the thermal stability of single diamonds with their intrinsic properties, which was then examined by a deviation-probability examination. The results illustrate that it is reasonable to take the Extrapolated Onset Temperature in DTA as the characteristic temperature for thermal stability (TS) of Ib-type synthetic single diamonds. The nitrogen content and grain shape regularity of diamonds are dominating factors. Likewise, grain size and compressive strength are minor factors. In addition, GM(1,5) can be used to predict the thermal stability of Ib-type synthetic single diamonds available. The precision rank of GM(1,5) is ‘GOOD’. 展开更多
关键词 synthetic single diamond thermal stability grey relationship analysis grey forecasting model
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The Modified GM( 1 , 1) Grey Forecast Model
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作者 Wang Chengzhang Guo Yaohuang Li Qiang (School of Economics and Management,Southwest Jiaotong University)Chengdu 61 0031 , China 《Journal of Modern Transportation》 1995年第2期157-162,共6页
Because the impacts of the factors such as some disturbances are graduallyadded into the system, the grey forecast results will deviate from the systemtrue value. To improve the forecast precision, Pro-Dens Julons pro... Because the impacts of the factors such as some disturbances are graduallyadded into the system, the grey forecast results will deviate from the systemtrue value. To improve the forecast precision, Pro-Dens Julons provided twomethfor-But they had not consider the impact of artificial disturbance. LiZhihua et al. of Qinghua Univ. presented another method. This paper revisesthe method and make it be a spocial case. 展开更多
关键词 grey forecast GM(1 1 ) model influential factor
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Application of Improved Grey Prediction Model to Petroleum Cost Forecasting 被引量:3
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作者 Li Jia Wang Baoyi Zhang Baosheng 《Petroleum Science》 SCIE CAS CSCD 2006年第2期89-92,共4页
The grey theory is a multidisciplinary and generic theory that deals with systems that lack adequate information and/or have only poor information. In this paper, an improved grey model using step function was propose... The grey theory is a multidisciplinary and generic theory that deals with systems that lack adequate information and/or have only poor information. In this paper, an improved grey model using step function was proposed. Petroleum cost forecast of the Henan oil field was used as the case study to test the efficiency and accuracy of the proposed method. According to the experimental results, the proposed method obviously could improve the prediction accuracy of the original grey model. 展开更多
关键词 grey forecast petroleum cost MUTATION smooth degree
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Hybrid grey model to forecast monitoring series with seasonality 被引量:3
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作者 王琪洁 廖新浩 +3 位作者 周永宏 邹峥嵘 朱建军 彭悦 《Journal of Central South University of Technology》 2005年第5期623-627,共5页
The grey forecasting model has been successfully applied to many fields. However, the precision of GM(1,1) model is not high. In order to remove the seasonal fluctuations in monitoring series before building GM(1,1) m... The grey forecasting model has been successfully applied to many fields. However, the precision of GM(1,1) model is not high. In order to remove the seasonal fluctuations in monitoring series before building GM(1,1) model, the forecasting series of GM(1,1) was built, and an inverse process was used to resume the seasonal fluctuations. Two deseasonalization methods were presented , i.e., seasonal index-based deseasonalization and standard normal distribution-based deseasonalization. They were combined with the GM(1,1) model to form hybrid grey models. A simple but practical method to further improve the forecasting results was also suggested. For comparison, a conventional periodic function model was investigated. The concept and algorithms were tested with four years monthly monitoring data. The results show that on the whole the seasonal index-GM(1,1) model outperform the conventional periodic function model and the conventional periodic function model outperform the SND-GM(1,1) model. The mean Absolute error and mean square error of seasonal index-GM(1,1) are 30.69% and 54.53% smaller than that of conventional periodic function model, respectively. The high accuracy, straightforward and easy implementation natures of the proposed hybrid seasonal index-grey model make it a powerful analysis technique for seasonal monitoring series. 展开更多
关键词 seasonal index GM(1 1) grey forecasting model time series
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The Further Development and Application of Grey Forecasting Model
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作者 LIN Chun-yanDepartment of Mathematics, Dalian University of Technology, Dalian 116024, China 《Systems Science and Systems Engineering》 CSCD 2002年第3期302-305,共4页
In this paper, the method which forecasts original sequences {x (0)(k)} with logarithmic function or with power function has been complemented, and the method which handles original sequences by logarithmic function-... In this paper, the method which forecasts original sequences {x (0)(k)} with logarithmic function or with power function has been complemented, and the method which handles original sequences by logarithmic function-power function transformation or by power function-logarithmic function transformation has been presented, then smooth degree and precision of forecasting of discrete data have been improved. 展开更多
关键词 grey forecasting power function transformation logarithmic function-power function transformation power function-logarithmic function transformation
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A novel fractional grey forecasting model with variable weighted buffer operator and its application in forecasting China's crude oil consumption
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作者 Yong Wang Yuyang Zhang +3 位作者 Rui Nie Pei Chi Xinbo He Lei Zhang 《Petroleum》 EI CSCD 2022年第2期139-157,共19页
Oil is an important strategic material and civil energy.Accurate prediction of oil consumption can provide basis for relevant departments to reasonably arrange crude oil production,oil import and export,and optimize t... Oil is an important strategic material and civil energy.Accurate prediction of oil consumption can provide basis for relevant departments to reasonably arrange crude oil production,oil import and export,and optimize the allocation of social resources.Therefore,a new grey model FENBGM(1,1)is proposed to predict oil consumption in China.Firstly,the grey effect of the traditional GM(1,1)model was transformed into a quadratic equation.Four different parameters were introduced to improve the accuracy of the model,and the new initial conditions were designed by optimizing the initial values by weighted buffer operator.Combined with the reprocessing of the original data,the scheme eliminates the random disturbance effect,improves the stability of the system sequence,and can effectively extract the potential pattern of future development.Secondly,the cumulative order of the new model was optimized by fractional cumulative generation operation.At the same time,the smoothness rate quasi-smoothness condition was introduced to verify the stability of the model,and the particle swarm optimization algorithm(PSO)was used to search the optimal parameters of the model to enhance the adaptability of the model.Based on the above improvements,the new combination prediction model overcomes the limitation of the traditional grey model and obtains more accurate and robust prediction results.Then,taking the petroleum consumption of China's manufacturing industry and transportation,storage and postal industry as an example,this paper verifies the validity of FENBGM(1,1)model,analyzes and forecasts China's crude oil consumption with several commonly used forecasting models,and uses FENBGM(1,1)model to forecast China's oil consumption in the next four years.The results show that FENBGM(1,1)model performs best in all cases.Finally,based on the prediction results of FENBGM(1,1)model,some reasonable suggestions are put forward for China's oil consumption planning. 展开更多
关键词 grey forecasting model Variable weighted buffer operator Particle swarm optimization Oil consumption forecast
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The Application of a Grey Markov Model to Forecasting Annual Maximum Water Levels at Hydrological Stations 被引量:12
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作者 DONG Sheng CHI Kun +1 位作者 ZHANG Qiyi ZHANG Xiangdong 《Journal of Ocean University of China》 SCIE CAS 2012年第1期13-17,共5页
Compared with traditional real-time forecasting,this paper proposes a Grey Markov Model(GMM) to forecast the maximum water levels at hydrological stations in the estuary area.The GMM combines the Grey System and Marko... Compared with traditional real-time forecasting,this paper proposes a Grey Markov Model(GMM) to forecast the maximum water levels at hydrological stations in the estuary area.The GMM combines the Grey System and Markov theory into a higher precision model.The GMM takes advantage of the Grey System to predict the trend values and uses the Markov theory to forecast fluctuation values,and thus gives forecast results involving two aspects of information.The procedure for forecasting annul maximum water levels with the GMM contains five main steps:1) establish the GM(1,1) model based on the data series;2) estimate the trend values;3) establish a Markov Model based on relative error series;4) modify the relative errors caused in step 2,and then obtain the relative errors of the second order estimation;5) compare the results with measured data and estimate the accuracy.The historical water level records(from 1960 to 1992) at Yuqiao Hydrological Station in the estuary area of the Haihe River near Tianjin,China are utilized to calibrate and verify the proposed model according to the above steps.Every 25 years' data are regarded as a hydro-sequence.Eight groups of simulated results show reasonable agreement between the predicted values and the measured data.The GMM is also applied to the 10 other hydrological stations in the same estuary.The forecast results for all of the hydrological stations are good or acceptable.The feasibility and effectiveness of this new forecasting model have been proved in this paper. 展开更多
关键词 grey Markov Model forecasting estuary disaster prevention maximum water level
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Improved grey prediction model based on exponential grey action quantity 被引量:17
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作者 YIN Kedong GENG Yan LI Xuemei 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2018年第3期560-570,共11页
With the passage of time, it has become important to investigate new methods for updating data to better fit the trends of the grey prediction model. The traditional GM(1,1) usually sets the grey action quantity as ... With the passage of time, it has become important to investigate new methods for updating data to better fit the trends of the grey prediction model. The traditional GM(1,1) usually sets the grey action quantity as a constant. Therefore, it cannot effectively fit the dynamic characteristics of the sequence, which results in the grey model having a low precision. The linear grey action quantity model cannot represent the index change law. This paper presents a grey action quantity model, the exponential optimization grey model(EOGM(1,1)), based on the exponential type of grey action quantity; it is constructed based on the exponential characteristics of the grey prediction model. The model can fully reflect the exponential characteristics of the simulation series with time. The exponential sequence has a higher fitting accuracy. The optimized result is verified using a numerical example for the fluctuating sequence and a case study for the index of the tertiary industry's GDP. The results show that the model improves the precision of the grey forecasting model and reduces the prediction error. 展开更多
关键词 exponential of grey action quantity optimal algorithm grey forecasting mathematical modeling
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Expansion modelling of discrete grey model based on multi-factor information aggregation 被引量:7
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作者 Naiming Xie Chaoyu Zhu Jing Zheng 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2014年第5期833-839,共7页
This paper aims to study a novel expansion discrete grey forecasting model, which could aggregate input information more effectively. In general, existing multi-factor grey forecasting models, such as one order and h ... This paper aims to study a novel expansion discrete grey forecasting model, which could aggregate input information more effectively. In general, existing multi-factor grey forecasting models, such as one order and h variables grey forecasting model (GM (1, h)), always aggregate the main system variable and independent variables in a linear form rather than a nonlinear form, while a nonlinear form could be used in more cases than the linear form. And the nonlinear form could aggregate collinear independent factors, which widely lie in many multi-factor forecasting problems. To overcome this problem, a new approach, named as the Solow residual method, is proposed to aggregate independent factors. And a new expansion model, feedback multi-factor discrete grey forecasting model based on the Solow residual method (abbreviated as FDGM (1, h)), is proposed accordingly. Then the feedback control equation and the parameters' solution of the FDGM (1, h) model are given. Finally, a real application is used to test the modelling accuracy of the FDGM (1, h) model. Results show that the FDGM (1, h) model is much better than the nonhomogeneous discrete grey forecasting model (NDGM) and the GM (1, h) model. 展开更多
关键词 multi-variable system Solow residual method dis crete grey forecasting model grey system theory (GST).
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Study of evolution forecast of the area of the Huanghe River mouth
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作者 Guo Yongsheng, Xu Xuegong, Fan Zhaomu, Wu Peihong and Zhu Xiaoge Department of Geography, Shandong Normal University, Jinan 250014, China Department of Geography, Peking University, Beijing 100871, China Remote Sensing Geology Department, Oil Exploration and Exploitation Scientific Research Institute, Beijing 100083, China 《Acta Oceanologica Sinica》 SCIE CAS CSCD 1993年第2期249-259,共11页
From 1979 to 1989, the current Qingshuigou course of the Huanghe River formed a sub - delta which resembles a beak extending into the Laizhou Bay. It covers 618 km2 in area. To meet the needs of developing and constru... From 1979 to 1989, the current Qingshuigou course of the Huanghe River formed a sub - delta which resembles a beak extending into the Laizhou Bay. It covers 618 km2 in area. To meet the needs of developing and constructing the Huanghe River Delta and under the presupposition of keeping the current course for 15-20 a, we forecast mainly by using the OM (1, 1) model that the front border of the sub-delta will be close to 119°30'E and its area will become 923 km2by the end of the year 2000. The Huanghe River will make land 760 km2 in area. 展开更多
关键词 Huanghe River mouth Markov chain forecasting method of grey number series
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Research on Ratio of New Energy Vehicles to Charging Piles in China 被引量:1
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作者 Zhiqiu Yu Shuo-Yan Chou 《Computer Systems Science & Engineering》 SCIE EI 2022年第9期963-984,共22页
With the widespread of new energy vehicles, charging piles have alsobeen continuously installed and constructed. In order to make the number of pilesmeet the needs of the development of new energy vehicles, this study... With the widespread of new energy vehicles, charging piles have alsobeen continuously installed and constructed. In order to make the number of pilesmeet the needs of the development of new energy vehicles, this study aims toapply the method of system dynamics and combined with the grey prediction theory to determine the parameters as well as to simulate and analyze the ratio ofvehicles to chargers. Through scenario analysis, it is predicted that by 2030, thisratio will gradually decrease from 1.79 to 1. In order to achieve this ratio as 1:1, itis necessary to speed up the construction of public charging station or privatecharging station. Due to global warming, the attitudes of countries towards fuelvehicles have become increasingly tough. There is huge uncertainty in the growthrate of electric vehicles. Therefore, it is recommended that the construction ofcharging station be deployed in advance to avoid hindering the development ofelectric vehicles in the future. 展开更多
关键词 New energy vehicles charging piles system dynamic grey forecasting
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Study on High Accuracy Hybrid Controller for Periodic Motion Control
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作者 张珂 王生泽 《Journal of Donghua University(English Edition)》 EI CAS 2010年第4期510-515,共6页
In order to realize high accuracy control for periodic motion,a hybrid controller with grey prediction was presented in this paper.Incorporating the grey prediction,repetitive control,and the traditional Proportional-... In order to realize high accuracy control for periodic motion,a hybrid controller with grey prediction was presented in this paper.Incorporating the grey prediction,repetitive control,and the traditional Proportional-Integral-Differential(PID)control,a design method of the grey prediction repetitive PID(GRPID)control algorithm was investigated,according to the characteristics of the periodic motion control.The hybrid control algorithm can estimate unsure parameters and disturbance of system using grey prediction,and compensate control in terms of the prediction results,and this may improve control quality and robustness of repetitive control for controlling periodic motion.An example was carried out to verify the feasibility of the controller.The simulation results show that this algorithm has better performances than that of the conventional repetitive control system.It indicates the presented control method is more suitable for control system of periodic motion. 展开更多
关键词 grey forecasting repetitive control Proportional-Integral-Differential(PID) control system periodic motion
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Coupling coordination and evolution of finance,economy and ecological environment:The case of Silk Road provinces
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作者 WANG Hai-gang LIU Ke ZHANG Fan 《Ecological Economy》 2022年第4期274-286,共13页
Based on the comparative analysis of the coupling mechanism between finance,economy and ecological environment,this paper uses the coupling coordination degree and grey prediction model to measure the comprehensive ev... Based on the comparative analysis of the coupling mechanism between finance,economy and ecological environment,this paper uses the coupling coordination degree and grey prediction model to measure the comprehensive evaluation value and coupling coordination degree of the financial,economic and ecological environment composite system of five provinces along the Silk Road in China from 2010 to 2019,and analyzes the evolution law of the coupling and coordinated development of finance,economy and ecological environment from the perspective of system coordinated development.The results show that:(1)The development of the financial and economic systems of the provinces along the Silk Road shows a relatively continuous and stable good trend,while the development of the ecosystem shows more obvious fluctuations.(2)In general,the overall level of the comprehensive evaluation of each system in the provinces along the route has shown a trend of improvement,but the level is not high.(3)During the investigation by provinces,it is found that the coordination level of the coupling coordination degree of finance,economy and ecological environment of each province is in three stages:moderate disorder,mild disorder,and imminent imbalance.However,Shaanxi Province has changed from imminent imbalance to barely coordination earlier,which indicates that there is regional heterogeneity in the three coupling coordination relationships among regions.(4)According to the calculation of the gray GM(1,1)model,the coupling coordination degree in Shaanxi Province will maintain a good upward trend and reach a intermediate coordination stage in 2023,while the other provinces will enter the barely coordination and primary coordination stages respectively with a slightly slower growth rate.Finally,based on the research conclusions,this paper puts forward some effective policy recommendations for the coordinated development of regional finance,economy and ecological environment,such as dredging the diffusion channels of regional financial resources,guiding market funds to participate in ecological project construction,and advocating the development of circular economy. 展开更多
关键词 FINANCE ecological environment coupling coordination degree grey forecasting Silk Road
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基于新型核与灰度序列的时滞GM(1,N)模型及其应用 被引量:1
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作者 熊萍萍 石佳 +1 位作者 姚天祥 闫书丽 《运筹与管理》 CSSCI CSCD 北大核心 2022年第12期93-98,共6页
为了解决GM(1,N)模型在新型核与灰度的基础上,对驱动项的延迟作用机理不明确的问题,将时滞参数引入到GM(1,N)模型的驱动项中,构建了基于新型核与灰度的时滞GM(1,N)模型,分析了时滞参数的辨识方法,讨论了新模型的建模机理。为了更好地对... 为了解决GM(1,N)模型在新型核与灰度的基础上,对驱动项的延迟作用机理不明确的问题,将时滞参数引入到GM(1,N)模型的驱动项中,构建了基于新型核与灰度的时滞GM(1,N)模型,分析了时滞参数的辨识方法,讨论了新模型的建模机理。为了更好地对该模型的有效性进行验证,将优化的时滞GM(1,N)模型对南京市的雾霾进行预测分析,选择GM(1,N)模型、一元回归模型与文中的优化模型进行对比。结果显示,优化模型对PM10浓度的拟合精度更高,且误差均控制在5%之内,从而验证了提出的优化模型适用于具有时滞特征数据的模拟和预测。 展开更多
关键词 灰色系统理论 GM(1 N)模型 时滞效应 新型核与灰度 雾霾预测
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Grey System Forecast for Firing Accuracy of Gun 被引量:1
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作者 CHENG Qi-yue, QIU Wan-huaSchool of Management, Beijing University of Aeronautics and Astronautics, Beijing 100083 《Journal of Systems Science and Systems Engineering》 SCIE EI CSCD 2001年第2期240-243,共4页
In this paper, the system and subsystem forecast models for firing accuracy have been built by means of theory of Grey System Forecast. It has provided a scientific forecasting method for micro-error-control and macro... In this paper, the system and subsystem forecast models for firing accuracy have been built by means of theory of Grey System Forecast. It has provided a scientific forecasting method for micro-error-control and macro-error-control and improving the firing accuracy. 展开更多
关键词 grey system forecast firing accuracy firing effect
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Forecasting of dissolved oxygen in the Guanting reservoir using an optimized NGBM(1,1) model 被引量:3
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作者 Yan An Zhihong Zou Yanfei Zhao 《Journal of Environmental Sciences》 SCIE EI CAS CSCD 2015年第3期158-164,共7页
An optimized nonlinear grey Bernoulli model was proposed by using a particle swarm optimization algorithm to solve the parameter optimization problem. In addition, each item in the first-order accumulated generating s... An optimized nonlinear grey Bernoulli model was proposed by using a particle swarm optimization algorithm to solve the parameter optimization problem. In addition, each item in the first-order accumulated generating sequence was set in turn as an initial condition to determine which alternative would yield the highest forecasting accuracy. To test the forecasting performance, the optimized models with different initial conditions were then used to simulate dissolved oxygen concentrations in the Guantlng reservoir inlet and outlet (China). The empirical results show that the optimized model can remarkably improve forecasting accuracy, and the particle swarm optimization technique is a good tool to solve parameter optimization problems. What's more, the optimized model with an initial condition that performs well in in-sample simulation may not do as well as in out-of-sample forecasting. 展开更多
关键词 Water quality forecasting Dissolved oxygen Nonlinear grey Bernoulli model Particle swarm optimization Initial condition
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