{"title":"基于ART-2神经模糊网络的火灾探测系统","authors":"Zhang Qing, Wang Shu","doi":"10.1109/ICOSP.1998.770871","DOIUrl":null,"url":null,"abstract":"The ART-2 neural network is a self-organized artificial network that operates according to adaptive resonance theory. A neuro-fuzzy network, which combines ART-2 and the fuzzy system in series, is presented and applied to fire detection. The results of experiments show that this system has a stronger ability to adapt to the environment than the backpropagation (BP) neural network. It can detect various standard test fires more rapidly and accurately, and has strong anti-interference capability.","PeriodicalId":145700,"journal":{"name":"ICSP '98. 1998 Fourth International Conference on Signal Processing (Cat. No.98TH8344)","volume":"87 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1998-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"A fire detection system based on ART-2 neuro-fuzzy network\",\"authors\":\"Zhang Qing, Wang Shu\",\"doi\":\"10.1109/ICOSP.1998.770871\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The ART-2 neural network is a self-organized artificial network that operates according to adaptive resonance theory. A neuro-fuzzy network, which combines ART-2 and the fuzzy system in series, is presented and applied to fire detection. The results of experiments show that this system has a stronger ability to adapt to the environment than the backpropagation (BP) neural network. It can detect various standard test fires more rapidly and accurately, and has strong anti-interference capability.\",\"PeriodicalId\":145700,\"journal\":{\"name\":\"ICSP '98. 1998 Fourth International Conference on Signal Processing (Cat. No.98TH8344)\",\"volume\":\"87 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1998-10-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ICSP '98. 1998 Fourth International Conference on Signal Processing (Cat. No.98TH8344)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICOSP.1998.770871\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ICSP '98. 1998 Fourth International Conference on Signal Processing (Cat. No.98TH8344)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICOSP.1998.770871","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A fire detection system based on ART-2 neuro-fuzzy network
The ART-2 neural network is a self-organized artificial network that operates according to adaptive resonance theory. A neuro-fuzzy network, which combines ART-2 and the fuzzy system in series, is presented and applied to fire detection. The results of experiments show that this system has a stronger ability to adapt to the environment than the backpropagation (BP) neural network. It can detect various standard test fires more rapidly and accurately, and has strong anti-interference capability.
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