Navreet Saini, B. S. Dhaliwal, Simranjit Kaur Josan
{"title":"基于遗传算法的选择性神经网络集成方法分析矩形微带天线","authors":"Navreet Saini, B. S. Dhaliwal, Simranjit Kaur Josan","doi":"10.1109/ICMOCE.2015.7489732","DOIUrl":null,"url":null,"abstract":"Harmony in variety i.e. unity without similarity is a concept inspired from ancient times. Thinkers propose a team approach based on the same concept for problem solving i.e. using a combined group of solvers to resolve a difficult problem. Neural network ensemble (NNE) is a concept based on the same approach. Multiple artificial neural networks (ANNs) are trained for the same dataset to give the appropriate measured resonant frequency from the relative parameters of rectangular microstrip antenna (MSA). The previous experimental works' MSA datasets have been used for training of ANNs. Genetic Algorithm (GA) is employed to compute the optimum subset of ANNs which perform better than rest available to constitute an ensemble. A model of resonant frequency of MSA is established by using this NNE approach and the results have been compared with some previous works.","PeriodicalId":352568,"journal":{"name":"2015 International Conference on Microwave, Optical and Communication Engineering (ICMOCE)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Genetic algorithm based selective neural network ensemble method to analyse rectangular microstrip antenna\",\"authors\":\"Navreet Saini, B. S. Dhaliwal, Simranjit Kaur Josan\",\"doi\":\"10.1109/ICMOCE.2015.7489732\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Harmony in variety i.e. unity without similarity is a concept inspired from ancient times. Thinkers propose a team approach based on the same concept for problem solving i.e. using a combined group of solvers to resolve a difficult problem. Neural network ensemble (NNE) is a concept based on the same approach. Multiple artificial neural networks (ANNs) are trained for the same dataset to give the appropriate measured resonant frequency from the relative parameters of rectangular microstrip antenna (MSA). The previous experimental works' MSA datasets have been used for training of ANNs. Genetic Algorithm (GA) is employed to compute the optimum subset of ANNs which perform better than rest available to constitute an ensemble. A model of resonant frequency of MSA is established by using this NNE approach and the results have been compared with some previous works.\",\"PeriodicalId\":352568,\"journal\":{\"name\":\"2015 International Conference on Microwave, Optical and Communication Engineering (ICMOCE)\",\"volume\":\"19 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 International Conference on Microwave, Optical and Communication Engineering (ICMOCE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICMOCE.2015.7489732\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 International Conference on Microwave, Optical and Communication Engineering (ICMOCE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICMOCE.2015.7489732","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Genetic algorithm based selective neural network ensemble method to analyse rectangular microstrip antenna
Harmony in variety i.e. unity without similarity is a concept inspired from ancient times. Thinkers propose a team approach based on the same concept for problem solving i.e. using a combined group of solvers to resolve a difficult problem. Neural network ensemble (NNE) is a concept based on the same approach. Multiple artificial neural networks (ANNs) are trained for the same dataset to give the appropriate measured resonant frequency from the relative parameters of rectangular microstrip antenna (MSA). The previous experimental works' MSA datasets have been used for training of ANNs. Genetic Algorithm (GA) is employed to compute the optimum subset of ANNs which perform better than rest available to constitute an ensemble. A model of resonant frequency of MSA is established by using this NNE approach and the results have been compared with some previous works.