基于遗传算法的人工神经网络结构进化设计

2010 Second International Conference on Computational Intelligence and Natural Computing Pub Date : 2010-11-22 DOI:10.1109/CINC.2010.5643748

N. Moharamzade, F. Farokhi

{"title":"基于遗传算法的人工神经网络结构进化设计","authors":"N. Moharamzade, F. Farokhi","doi":"10.1109/CINC.2010.5643748","DOIUrl":null,"url":null,"abstract":"Determining the optimum structure for an Artificial Network is an important design step in almost all the artificial intelligence systems which are based on Neural or neuro-fuzzy networks. In this paper a genetic algorithm based solution is presented and tested over real world databases and for single layer and multiple layer networks and it has been shown that the determined network structures has the best accuracy and the optimized topology as well.","PeriodicalId":227004,"journal":{"name":"2010 Second International Conference on Computational Intelligence and Natural Computing","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2010-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Evolutionary design of ANN structure using genetic algorithm\",\"authors\":\"N. Moharamzade, F. Farokhi\",\"doi\":\"10.1109/CINC.2010.5643748\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Determining the optimum structure for an Artificial Network is an important design step in almost all the artificial intelligence systems which are based on Neural or neuro-fuzzy networks. In this paper a genetic algorithm based solution is presented and tested over real world databases and for single layer and multiple layer networks and it has been shown that the determined network structures has the best accuracy and the optimized topology as well.\",\"PeriodicalId\":227004,\"journal\":{\"name\":\"2010 Second International Conference on Computational Intelligence and Natural Computing\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-11-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 Second International Conference on Computational Intelligence and Natural Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CINC.2010.5643748\",\"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 Second International Conference on Computational Intelligence and Natural Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CINC.2010.5643748","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 1

摘要

在几乎所有基于神经网络或神经模糊网络的人工智能系统中，确定人工网络的最优结构是一个重要的设计步骤。本文提出了一种基于遗传算法的解决方案，并在实际数据库以及单层和多层网络上进行了测试，结果表明，所确定的网络结构具有最佳的精度和优化的拓扑结构。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文

微信好友朋友圈 QQ好友复制链接

本刊更多论文

Evolutionary design of ANN structure using genetic algorithm

Determining the optimum structure for an Artificial Network is an important design step in almost all the artificial intelligence systems which are based on Neural or neuro-fuzzy networks. In this paper a genetic algorithm based solution is presented and tested over real world databases and for single layer and multiple layer networks and it has been shown that the determined network structures has the best accuracy and the optimized topology as well.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

2010 Second International Conference on Computational Intelligence and Natural Computing

自引率

0.00%

发文量