Accurate wind speed prediction has been becoming an indispensable technology in system security, wind energy utilization, and power grid dispatching in recent years. However, it is an arduous task to predict wind speed due to its variable and random characteristics. For the objective to enhance the performance of forecasting short-term wind speed, this work puts forward a hybrid deep learning model mixing time series decomposition algorithm and gated recurrent unit (GRU). The time series decomposition algorithm combines the following two parts: (1) the complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN), and (2) wavelet packet decomposition (WPD). Firstly, the normalized wind speed time series (WSTS) are handled by CEEMDAN to gain pure fixed-frequency components and a residual signal. The WPD algorithm conducts the second-order decomposition to the first component that contains complex and high frequency signal of raw WSTS. Finally, GRU networks are established for all the relevant components of the signals, and the predicted wind speeds are obtained by superimposing the prediction of each component. Results from two case studies, adopting wind data from laboratory and wind farm, respectively, suggest that the related trend of the WSTS can be separated effectively by the proposed time series decomposition algorithm, and the accuracy of short-time wind speed prediction can be heightened significantly mixing the time series decomposition algorithm and GRU networks.
{"title":"Hybrid Deep Learning Model for Short-Term Wind Speed Forecasting Based on Time Series Decomposition and Gated Recurrent Unit","authors":"Changtong Wang;Zhaohua Liu;Hualiang Wei;Lei Chen;Hongqiang Zhang","doi":"10.23919/CSMS.2021.0026","DOIUrl":"https://doi.org/10.23919/CSMS.2021.0026","url":null,"abstract":"Accurate wind speed prediction has been becoming an indispensable technology in system security, wind energy utilization, and power grid dispatching in recent years. However, it is an arduous task to predict wind speed due to its variable and random characteristics. For the objective to enhance the performance of forecasting short-term wind speed, this work puts forward a hybrid deep learning model mixing time series decomposition algorithm and gated recurrent unit (GRU). The time series decomposition algorithm combines the following two parts: (1) the complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN), and (2) wavelet packet decomposition (WPD). Firstly, the normalized wind speed time series (WSTS) are handled by CEEMDAN to gain pure fixed-frequency components and a residual signal. The WPD algorithm conducts the second-order decomposition to the first component that contains complex and high frequency signal of raw WSTS. Finally, GRU networks are established for all the relevant components of the signals, and the predicted wind speeds are obtained by superimposing the prediction of each component. Results from two case studies, adopting wind data from laboratory and wind farm, respectively, suggest that the related trend of the WSTS can be separated effectively by the proposed time series decomposition algorithm, and the accuracy of short-time wind speed prediction can be heightened significantly mixing the time series decomposition algorithm and GRU networks.","PeriodicalId":65786,"journal":{"name":"复杂系统建模与仿真(英文)","volume":"1 4","pages":"308-321"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/9420428/9673697/09673701.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49945130","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The supply of emergency materials is the fundament of emergency rescues. In view of the demand for emergency materials in major calamities, in this paper, a system dynamics model of emergency materials is constructed from the perspectives of wartime and peacetime. By setting and controlling the relevant parameters and variables, the influence of a variable on the demand and supply of emergency materials and the influence of government strategies on the quantity and provision of emergency material supply are analyzed. We explore the measures that can better ensure the supply to stabilize the social and economic security of the country. The results show that the emergency degree of an event will lead to increases in the amount of government expenditures and in the duration of such expenditures. Meanwhile, the increase in emergency cases will increase the variation range of the supply and demand deviation curve, lengthen the response time to demand, and fasten the growth trend of material supply. The Chinese government adopts comprehensive regulation and control mode, which make the supply and demand reach the equilibrium state more than twice as fast as other control methods. In addition, the promotion of publicity will improve the number of civil materials. A high inflation rate will lead to high imports of government materials, which will consequently affect the supply of emergency materials. The above research findings have important reference significance for the government's emergency materials management.
{"title":"Emergency Supply Control from the Perspectives of Peacetime and Wartime: A System Dynamics Simulation","authors":"Yuqing Qi;Xinglei Zhao;Heba El-Sayed;Bin Wu","doi":"10.23919/CSMS.2021.0016","DOIUrl":"10.23919/CSMS.2021.0016","url":null,"abstract":"The supply of emergency materials is the fundament of emergency rescues. In view of the demand for emergency materials in major calamities, in this paper, a system dynamics model of emergency materials is constructed from the perspectives of wartime and peacetime. By setting and controlling the relevant parameters and variables, the influence of a variable on the demand and supply of emergency materials and the influence of government strategies on the quantity and provision of emergency material supply are analyzed. We explore the measures that can better ensure the supply to stabilize the social and economic security of the country. The results show that the emergency degree of an event will lead to increases in the amount of government expenditures and in the duration of such expenditures. Meanwhile, the increase in emergency cases will increase the variation range of the supply and demand deviation curve, lengthen the response time to demand, and fasten the growth trend of material supply. The Chinese government adopts comprehensive regulation and control mode, which make the supply and demand reach the equilibrium state more than twice as fast as other control methods. In addition, the promotion of publicity will improve the number of civil materials. A high inflation rate will lead to high imports of government materials, which will consequently affect the supply of emergency materials. The above research findings have important reference significance for the government's emergency materials management.","PeriodicalId":65786,"journal":{"name":"复杂系统建模与仿真(英文)","volume":"1 4","pages":"322-334"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/9420428/9673697/09673702.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43787918","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this study, simulation software AnyLogic was used to establish a station simulation model for a metro line. First, a basic model of the environment of the metro station was drawn, and accordingly, reasonable assumptions and simplifications were proposed. Then, a diagram of the passenger walking path was created and the simulation variables and functions for passenger flow management were designed. Considering Youfangqiao Station of Nanjing Metro Line 2 in China as an example, the real passenger flow data of this station were statistically analyzed. To simulate the station passenger flow management, input parameters such as the passenger space diameter, passenger flow generation rate, delay rate of automatic fare collection equipment and security check machine, and the number of gates were considered. Passenger flow management was optimized for the morning and evening peak periods, and reasonable suggestions were proposed based on the optimization results, providing a theoretical basis for the construction planning and pre-evaluation of station operation capacities of urban rail transit systems.
{"title":"Study on Optimization of Passenger Flow at a Metro Station Based on AnyLogic—Case Study of Youfangqiao Station of Nanjing Metro Line 2","authors":"Weihong Ni;Jiahao Yu;Hong Cai;Meimei Bai;Bin Wu","doi":"10.23919/CSMS.2021.0009","DOIUrl":"10.23919/CSMS.2021.0009","url":null,"abstract":"In this study, simulation software AnyLogic was used to establish a station simulation model for a metro line. First, a basic model of the environment of the metro station was drawn, and accordingly, reasonable assumptions and simplifications were proposed. Then, a diagram of the passenger walking path was created and the simulation variables and functions for passenger flow management were designed. Considering Youfangqiao Station of Nanjing Metro Line 2 in China as an example, the real passenger flow data of this station were statistically analyzed. To simulate the station passenger flow management, input parameters such as the passenger space diameter, passenger flow generation rate, delay rate of automatic fare collection equipment and security check machine, and the number of gates were considered. Passenger flow management was optimized for the morning and evening peak periods, and reasonable suggestions were proposed based on the optimization results, providing a theoretical basis for the construction planning and pre-evaluation of station operation capacities of urban rail transit systems.","PeriodicalId":65786,"journal":{"name":"复杂系统建模与仿真(英文)","volume":"1 3","pages":"242-252"},"PeriodicalIF":0.0,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/9420428/9600623/09600622.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41506043","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Numerous performance indicators exist for semiconductor manufacturing systems. Several studies have been conducted regarding the performance optimization of semiconductor manufacturing systems. However, because of the complex manufacturing processes, potential complementary or inhibitory correlations may exist among performance indicators, which are difficult to demonstrate specifically. To analyze the correlation between the performance indicators, this study proposes a performance evaluation system based on the mathematical significance of each performance indicator to design statistical schemes. Several samples can be obtained by conducting simulation experiments through the performance evaluation system. The Pearson correlation coefficient method and canonical correlation analysis are used on the received samples to analyze linear correlations between the performance indicators. Through the investigation, we found that linear and other complex correlations exist between the performance indicators. This finding can contribute to our future studies regarding performance optimization for the scheduling problems of semiconductor manufacturing.
{"title":"Evaluation System and Correlation Analysis for Determining the Performance of a Semiconductor Manufacturing System","authors":"Qingyun Yu;Li Li;Hui Zhao;Ying Liu;Kuo-Yi Lin","doi":"10.23919/CSMS.2021.0015","DOIUrl":"10.23919/CSMS.2021.0015","url":null,"abstract":"Numerous performance indicators exist for semiconductor manufacturing systems. Several studies have been conducted regarding the performance optimization of semiconductor manufacturing systems. However, because of the complex manufacturing processes, potential complementary or inhibitory correlations may exist among performance indicators, which are difficult to demonstrate specifically. To analyze the correlation between the performance indicators, this study proposes a performance evaluation system based on the mathematical significance of each performance indicator to design statistical schemes. Several samples can be obtained by conducting simulation experiments through the performance evaluation system. The Pearson correlation coefficient method and canonical correlation analysis are used on the received samples to analyze linear correlations between the performance indicators. Through the investigation, we found that linear and other complex correlations exist between the performance indicators. This finding can contribute to our future studies regarding performance optimization for the scheduling problems of semiconductor manufacturing.","PeriodicalId":65786,"journal":{"name":"复杂系统建模与仿真(英文)","volume":"1 3","pages":"218-231"},"PeriodicalIF":0.0,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/9420428/9600623/09600619.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41594524","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Introducing InterSatellite Links (ISLs) is a major trend in new-generation Global Navigation Satellite Systems (GNSSs). Data transmission scheduling is a crucial problem in the study of ISL management. The existing research on intersatellite data transmission has not considered the capacities of ISL bandwidth. Thus, the current study is the first to describe the intersatellite data transmission scheduling problem with capacity restrictions in GNSSs. A model conversion strategy is designed to model the aforementioned problem as a length-bounded single-path multicommodity flow problem. An integer programming model is constructed to minimize the maximal sum of flows on each intersatellite edge; this minimization is equivalent to minimizing the maximal occupied ISL bandwidth. An iterated tree search algorithm is proposed to resolve the problem, and two ranking rules are designed to guide the search. Experiments based on the BeiDou satellite constellation are designed, and results demonstrate the effectiveness of the proposed model and algorithm.
{"title":"Multicommodity Flow Modeling for the Data Transmission Scheduling Problem in Navigation Satellite Systems","authors":"Jungang Yan;Lining Xing;Chao Li;Zhongshan Zhang","doi":"10.23919/CSMS.2021.0019","DOIUrl":"10.23919/CSMS.2021.0019","url":null,"abstract":"Introducing InterSatellite Links (ISLs) is a major trend in new-generation Global Navigation Satellite Systems (GNSSs). Data transmission scheduling is a crucial problem in the study of ISL management. The existing research on intersatellite data transmission has not considered the capacities of ISL bandwidth. Thus, the current study is the first to describe the intersatellite data transmission scheduling problem with capacity restrictions in GNSSs. A model conversion strategy is designed to model the aforementioned problem as a length-bounded single-path multicommodity flow problem. An integer programming model is constructed to minimize the maximal sum of flows on each intersatellite edge; this minimization is equivalent to minimizing the maximal occupied ISL bandwidth. An iterated tree search algorithm is proposed to resolve the problem, and two ranking rules are designed to guide the search. Experiments based on the BeiDou satellite constellation are designed, and results demonstrate the effectiveness of the proposed model and algorithm.","PeriodicalId":65786,"journal":{"name":"复杂系统建模与仿真(英文)","volume":"1 3","pages":"232-241"},"PeriodicalIF":0.0,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/9420428/9600623/09600644.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43333593","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Wenqiang Zhang;Wenlin Hou;Chen Li;Weidong Yang;Mitsuo Gen
The Mixed No-Idle Flow-shop Scheduling Problem (MNIFSP) is an extension of flow-shop scheduling, which has practical significance and application prospects in production scheduling. To improve the efficacy of solving the complicated multiobjective MNIFSP, a MultiDirection Update (MDU) based Multiobjective Particle Swarm Optimization (MDU-MoPSO) is proposed in this study. For the biobjective optimization problem of the MNIFSP with minimization of makespan and total processing time, the MDU strategy divides particles into three subgroups according to a hybrid selection mechanism. Each subgroup prefers one convergence direction. Two subgroups are individually close to the two edge areas of the Pareto Front (PF) and serve two objectives, whereas the other one approaches the central area of the PF, preferring the two objectives at the same time. The MDU-MoPSO adopts a job sequence representation method and an exchange sequence-based particle update operation, which can better reflect the characteristics of sequence differences among particles. The MDU-MoPSO updates the particle in multiple directions and interacts in each direction, which speeds up the convergence while maintaining a good distribution performance. The experimental results and comparison of six classical evolutionary algorithms for various benchmark problems demonstrate the effectiveness of the proposed algorithm.
{"title":"Multidirection Update-Based Multiobjective Particle Swarm Optimization for Mixed No-Idle Flow-Shop Scheduling Problem","authors":"Wenqiang Zhang;Wenlin Hou;Chen Li;Weidong Yang;Mitsuo Gen","doi":"10.23919/CSMS.2021.0017","DOIUrl":"10.23919/CSMS.2021.0017","url":null,"abstract":"The Mixed No-Idle Flow-shop Scheduling Problem (MNIFSP) is an extension of flow-shop scheduling, which has practical significance and application prospects in production scheduling. To improve the efficacy of solving the complicated multiobjective MNIFSP, a MultiDirection Update (MDU) based Multiobjective Particle Swarm Optimization (MDU-MoPSO) is proposed in this study. For the biobjective optimization problem of the MNIFSP with minimization of makespan and total processing time, the MDU strategy divides particles into three subgroups according to a hybrid selection mechanism. Each subgroup prefers one convergence direction. Two subgroups are individually close to the two edge areas of the Pareto Front (PF) and serve two objectives, whereas the other one approaches the central area of the PF, preferring the two objectives at the same time. The MDU-MoPSO adopts a job sequence representation method and an exchange sequence-based particle update operation, which can better reflect the characteristics of sequence differences among particles. The MDU-MoPSO updates the particle in multiple directions and interacts in each direction, which speeds up the convergence while maintaining a good distribution performance. The experimental results and comparison of six classical evolutionary algorithms for various benchmark problems demonstrate the effectiveness of the proposed algorithm.","PeriodicalId":65786,"journal":{"name":"复杂系统建模与仿真(英文)","volume":"1 3","pages":"176-197"},"PeriodicalIF":0.0,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/9420428/9600623/09600624.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48775142","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Call for Papers: Special Issue on Computational Intelligence Methods for Big Data Analytics under Uncertain Environments","authors":"","doi":"10.23919/CSMS.2021.0021","DOIUrl":"10.23919/CSMS.2021.0021","url":null,"abstract":"","PeriodicalId":65786,"journal":{"name":"复杂系统建模与仿真(英文)","volume":"1 3","pages":"255-256"},"PeriodicalIF":0.0,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/9420428/9600623/09600645.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45988333","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Call for Papers: Special Issue on Intelligent Optimization, Modeling, and Simulation with Knowledge for Complex Systems","authors":"","doi":"10.23919/CSMS.2021.0020","DOIUrl":"10.23919/CSMS.2021.0020","url":null,"abstract":"","PeriodicalId":65786,"journal":{"name":"复杂系统建模与仿真(英文)","volume":"1 3","pages":"253-254"},"PeriodicalIF":0.0,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/9420428/9600623/09600646.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45665536","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
To meet the multi-cooperation production demand of enterprises, the distributed permutation flow shop scheduling problem (DPFSP) has become the frontier research in the field of manufacturing systems. In this paper, we investigate the DPFSP by minimizing a makespan criterion under the constraint of sequence-dependent setup times. To solve DPFSPs, significant developments of some metaheuristic algorithms are necessary. In this context, a simple and effective improved iterated greedy (NIG) algorithm is proposed to minimize makespan in DPFSPs. According to the features of DPFSPs, a two-stage local search based on single job swapping and job block swapping within the key factory is designed in the proposed algorithm. We compare the proposed algorithm with state-of-the-art algorithms, including the iterative greedy algorithm (2019), iterative greedy proposed by Ruiz and Pan (2019), discrete differential evolution algorithm (2018), discrete artificial bee colony (2018), and artificial chemical reaction optimization (2017). Simulation results show that NIG outperforms the compared algorithms.
{"title":"Distributed Flow Shop Scheduling with Sequence-Dependent Setup Times Using an Improved Iterated Greedy Algorithm","authors":"Xue Han;Yuyan Han;Qingda Chen;Junqing Li;Hongyan Sang;Yiping Liu;Quanke Pan;Yusuke Nojima","doi":"10.23919/CSMS.2021.0018","DOIUrl":"10.23919/CSMS.2021.0018","url":null,"abstract":"To meet the multi-cooperation production demand of enterprises, the distributed permutation flow shop scheduling problem (DPFSP) has become the frontier research in the field of manufacturing systems. In this paper, we investigate the DPFSP by minimizing a makespan criterion under the constraint of sequence-dependent setup times. To solve DPFSPs, significant developments of some metaheuristic algorithms are necessary. In this context, a simple and effective improved iterated greedy (NIG) algorithm is proposed to minimize makespan in DPFSPs. According to the features of DPFSPs, a two-stage local search based on single job swapping and job block swapping within the key factory is designed in the proposed algorithm. We compare the proposed algorithm with state-of-the-art algorithms, including the iterative greedy algorithm (2019), iterative greedy proposed by Ruiz and Pan (2019), discrete differential evolution algorithm (2018), discrete artificial bee colony (2018), and artificial chemical reaction optimization (2017). Simulation results show that NIG outperforms the compared algorithms.","PeriodicalId":65786,"journal":{"name":"复杂系统建模与仿真(英文)","volume":"1 3","pages":"198-217"},"PeriodicalIF":0.0,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/9420428/9600623/09600643.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43796166","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：