{"title":"基于文化粒子群优化算法的水电站优化运行分析","authors":"Xin Ma","doi":"10.1109/IEEC.2010.5533269","DOIUrl":null,"url":null,"abstract":"Hydropower station optimal operation is a complex nonlinear combinatorial optimization problem. A novel culture particle swarm optimization algorithm for optimal operation problem in hydropower station is suggested. A local random search operator to achieve knowledge structure in belief space and enhance the population diversity and increase the capacity of global search with the introduction of culture algorithm, The simulation results of culture particle swarm optimization algorithm compares with particle swarm optimization algorithm and shows that this new algorithm can overcome the shortcomings of the traditional particle swarm algorithm and to gain better convergence speed and computational accuracy.","PeriodicalId":307678,"journal":{"name":"2010 2nd International Symposium on Information Engineering and Electronic Commerce","volume":"223 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Analysis on Optimal Operation of Hydropower Station Based on Cultural Particle Swarm Optimization Algorithm\",\"authors\":\"Xin Ma\",\"doi\":\"10.1109/IEEC.2010.5533269\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Hydropower station optimal operation is a complex nonlinear combinatorial optimization problem. A novel culture particle swarm optimization algorithm for optimal operation problem in hydropower station is suggested. A local random search operator to achieve knowledge structure in belief space and enhance the population diversity and increase the capacity of global search with the introduction of culture algorithm, The simulation results of culture particle swarm optimization algorithm compares with particle swarm optimization algorithm and shows that this new algorithm can overcome the shortcomings of the traditional particle swarm algorithm and to gain better convergence speed and computational accuracy.\",\"PeriodicalId\":307678,\"journal\":{\"name\":\"2010 2nd International Symposium on Information Engineering and Electronic Commerce\",\"volume\":\"223 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-07-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 2nd International Symposium on Information Engineering and Electronic Commerce\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IEEC.2010.5533269\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 2nd International Symposium on Information Engineering and Electronic Commerce","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IEEC.2010.5533269","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Analysis on Optimal Operation of Hydropower Station Based on Cultural Particle Swarm Optimization Algorithm
Hydropower station optimal operation is a complex nonlinear combinatorial optimization problem. A novel culture particle swarm optimization algorithm for optimal operation problem in hydropower station is suggested. A local random search operator to achieve knowledge structure in belief space and enhance the population diversity and increase the capacity of global search with the introduction of culture algorithm, The simulation results of culture particle swarm optimization algorithm compares with particle swarm optimization algorithm and shows that this new algorithm can overcome the shortcomings of the traditional particle swarm algorithm and to gain better convergence speed and computational accuracy.