{"title":"基于前馈神经网络的蜂窝移动无线电系统动态信道分配","authors":"P.T.H. Chan, M. Palaniswami, D. Everitt","doi":"10.1109/IJCNN.1991.170567","DOIUrl":null,"url":null,"abstract":"Conventional dynamic channel assignment schemes are both time-consuming and algorithmically complex. An alternative approach using a multilayered feedforward neural network model is examined. The results of the neural network approach are compared with those of a maximum packing strategy technique. The comparison shows that the neural networks approach is well-suited to the dynamic channel allocation problem.<<ETX>>","PeriodicalId":211135,"journal":{"name":"[Proceedings] 1991 IEEE International Joint Conference on Neural Networks","volume":"24 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1991-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"Dynamic channel assignment for cellular mobile radio system using feedforward neural networks\",\"authors\":\"P.T.H. Chan, M. Palaniswami, D. Everitt\",\"doi\":\"10.1109/IJCNN.1991.170567\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Conventional dynamic channel assignment schemes are both time-consuming and algorithmically complex. An alternative approach using a multilayered feedforward neural network model is examined. The results of the neural network approach are compared with those of a maximum packing strategy technique. The comparison shows that the neural networks approach is well-suited to the dynamic channel allocation problem.<<ETX>>\",\"PeriodicalId\":211135,\"journal\":{\"name\":\"[Proceedings] 1991 IEEE International Joint Conference on Neural Networks\",\"volume\":\"24 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1991-11-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"[Proceedings] 1991 IEEE International Joint Conference on Neural Networks\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IJCNN.1991.170567\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"[Proceedings] 1991 IEEE International Joint Conference on Neural Networks","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IJCNN.1991.170567","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Dynamic channel assignment for cellular mobile radio system using feedforward neural networks
Conventional dynamic channel assignment schemes are both time-consuming and algorithmically complex. An alternative approach using a multilayered feedforward neural network model is examined. The results of the neural network approach are compared with those of a maximum packing strategy technique. The comparison shows that the neural networks approach is well-suited to the dynamic channel allocation problem.<>