{"title":"平行进化非对称子产品模糊神经推理系统:一种孤岛模型方法","authors":"Lotika Singh, Satish Kumar","doi":"10.1109/ICCTA.2007.100","DOIUrl":null,"url":null,"abstract":"This paper introduces an island model approach for differential evolution (DE) learning in asymmetric subsethood product fuzzy neural inference system (ASuPFuNIS). In the island model, each island executes an independent DE and maintains its own sub-population for search. The migration model scheme has been implemented here to parallelize ASuPFuNIS. The parallelization strategy presented here is compared with the master-slave approach","PeriodicalId":308247,"journal":{"name":"2007 International Conference on Computing: Theory and Applications (ICCTA'07)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"Parallel Evolutionary Asymmetric Subsethood Product Fuzzy-Neural Inference System: An Island Model Approach\",\"authors\":\"Lotika Singh, Satish Kumar\",\"doi\":\"10.1109/ICCTA.2007.100\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper introduces an island model approach for differential evolution (DE) learning in asymmetric subsethood product fuzzy neural inference system (ASuPFuNIS). In the island model, each island executes an independent DE and maintains its own sub-population for search. The migration model scheme has been implemented here to parallelize ASuPFuNIS. The parallelization strategy presented here is compared with the master-slave approach\",\"PeriodicalId\":308247,\"journal\":{\"name\":\"2007 International Conference on Computing: Theory and Applications (ICCTA'07)\",\"volume\":\"6 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-03-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2007 International Conference on Computing: Theory and Applications (ICCTA'07)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCTA.2007.100\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2007 International Conference on Computing: Theory and Applications (ICCTA'07)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCTA.2007.100","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Parallel Evolutionary Asymmetric Subsethood Product Fuzzy-Neural Inference System: An Island Model Approach
This paper introduces an island model approach for differential evolution (DE) learning in asymmetric subsethood product fuzzy neural inference system (ASuPFuNIS). In the island model, each island executes an independent DE and maintains its own sub-population for search. The migration model scheme has been implemented here to parallelize ASuPFuNIS. The parallelization strategy presented here is compared with the master-slave approach