{"title":"极大极小规划中的神经网络","authors":"S. Osowski","doi":"10.1109/CNNA.1990.207531","DOIUrl":null,"url":null,"abstract":"The application of the neural computing network concept to the minimax optimization is presented. According to the method the minimax programming problem is first transformed to the standard single-objective optimization problem and then solved by transforming it to the set of ordinary differential equations. The clustered connection-type interpretation of the neural-based minimax approach is given. The numerical results of some chosen examples are also presented.<<ETX>>","PeriodicalId":142909,"journal":{"name":"IEEE International Workshop on Cellular Neural Networks and their Applications","volume":"47 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1990-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Neural networks in minimax programming\",\"authors\":\"S. Osowski\",\"doi\":\"10.1109/CNNA.1990.207531\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The application of the neural computing network concept to the minimax optimization is presented. According to the method the minimax programming problem is first transformed to the standard single-objective optimization problem and then solved by transforming it to the set of ordinary differential equations. The clustered connection-type interpretation of the neural-based minimax approach is given. The numerical results of some chosen examples are also presented.<<ETX>>\",\"PeriodicalId\":142909,\"journal\":{\"name\":\"IEEE International Workshop on Cellular Neural Networks and their Applications\",\"volume\":\"47 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1990-12-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE International Workshop on Cellular Neural Networks and their Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CNNA.1990.207531\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE International Workshop on Cellular Neural Networks and their Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CNNA.1990.207531","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The application of the neural computing network concept to the minimax optimization is presented. According to the method the minimax programming problem is first transformed to the standard single-objective optimization problem and then solved by transforming it to the set of ordinary differential equations. The clustered connection-type interpretation of the neural-based minimax approach is given. The numerical results of some chosen examples are also presented.<>
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