{"title":"基于萤火虫算法的超混沌Chen-Lee系统参数辨识","authors":"Farid Shayeteh, R. K. Moghaddam","doi":"10.5899/2018/JSCA-00096","DOIUrl":null,"url":null,"abstract":"Parameter identification for chaotic systems is one of the crucial issues in nonlinear science, which can be raised as a multi-dimensional optimization problem. In this article, parameter estimation of hyperchaotic Chen-Lee system was performed for the first time using the metaheuristic firefly algorithm. Firefly algorithm is a nature-inspired metaheuristic and optimization algorithm. This algorithm has been provided by Yang and inspired by natural behavior of fireflies of light emission. The efficiency of the firefly algorithm has been compared with the particle swarm optimization (PSO) algorithm. The results of the simulation conducted on the model indicated high accuracy and speed of the firefly algorithm in parameter estimation of hyperchaotic systems.","PeriodicalId":38638,"journal":{"name":"International Journal of Advances in Soft Computing and its Applications","volume":"71 1","pages":"1-12"},"PeriodicalIF":0.0000,"publicationDate":"2018-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Parameter Identification of Hyperchaotic Chen-Lee System Using Firefly Algorithm\",\"authors\":\"Farid Shayeteh, R. K. Moghaddam\",\"doi\":\"10.5899/2018/JSCA-00096\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Parameter identification for chaotic systems is one of the crucial issues in nonlinear science, which can be raised as a multi-dimensional optimization problem. In this article, parameter estimation of hyperchaotic Chen-Lee system was performed for the first time using the metaheuristic firefly algorithm. Firefly algorithm is a nature-inspired metaheuristic and optimization algorithm. This algorithm has been provided by Yang and inspired by natural behavior of fireflies of light emission. The efficiency of the firefly algorithm has been compared with the particle swarm optimization (PSO) algorithm. The results of the simulation conducted on the model indicated high accuracy and speed of the firefly algorithm in parameter estimation of hyperchaotic systems.\",\"PeriodicalId\":38638,\"journal\":{\"name\":\"International Journal of Advances in Soft Computing and its Applications\",\"volume\":\"71 1\",\"pages\":\"1-12\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Advances in Soft Computing and its Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5899/2018/JSCA-00096\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Computer Science\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Advances in Soft Computing and its Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5899/2018/JSCA-00096","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Computer Science","Score":null,"Total":0}
Parameter Identification of Hyperchaotic Chen-Lee System Using Firefly Algorithm
Parameter identification for chaotic systems is one of the crucial issues in nonlinear science, which can be raised as a multi-dimensional optimization problem. In this article, parameter estimation of hyperchaotic Chen-Lee system was performed for the first time using the metaheuristic firefly algorithm. Firefly algorithm is a nature-inspired metaheuristic and optimization algorithm. This algorithm has been provided by Yang and inspired by natural behavior of fireflies of light emission. The efficiency of the firefly algorithm has been compared with the particle swarm optimization (PSO) algorithm. The results of the simulation conducted on the model indicated high accuracy and speed of the firefly algorithm in parameter estimation of hyperchaotic systems.
期刊介绍：
The aim of this journal is to provide a lively forum for the communication of original research papers and timely review articles on Advances in Soft Computing and Its Applications. IJASCA will publish only articles of the highest quality. Submissions will be evaluated on their originality and significance. IJASCA invites submissions in all areas of Soft Computing and Its Applications. The scope of the journal includes, but is not limited to: √ Soft Computing Fundamental and Optimization √ Soft Computing for Big Data Era √ GPU Computing for Machine Learning √ Soft Computing Modeling for Perception and Spiritual Intelligence √ Soft Computing and Agents Technology √ Soft Computing in Computer Graphics √ Soft Computing and Pattern Recognition √ Soft Computing in Biomimetic Pattern Recognition √ Data mining for Social Network Data √ Spatial Data Mining & Information Retrieval √ Intelligent Software Agent Systems and Architectures √ Advanced Soft Computing and Multi-Objective Evolutionary Computation √ Perception-Based Intelligent Decision Systems √ Spiritual-Based Intelligent Systems √ Soft Computing in Industry ApplicationsOther issues related to the Advances of Soft Computing in various applications.
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