{"title":"基于聚类算法和模糊神经网络的煤矿瓦斯涌出预测","authors":"Xiaoyue Liu, Yiwen Liu, Zhenyou Zhang, Lin Zhang","doi":"10.1109/IFOST.2011.6021183","DOIUrl":null,"url":null,"abstract":"Coal mining gas emission was constrained by many factors. Considering the eight main factors of gas emission, using ant colony clustering and fuzzy C means clustering applied to data pre-processing, determine the membership function of emission. Fuzzy rules extracted from the data sample, establish a fuzzy neural network prediction system of coal mining gas emission.","PeriodicalId":20466,"journal":{"name":"Proceedings of 2011 6th International Forum on Strategic Technology","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2011-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Prediction of coal mining gas emission based on clustering algorithm and fuzzy neural network\",\"authors\":\"Xiaoyue Liu, Yiwen Liu, Zhenyou Zhang, Lin Zhang\",\"doi\":\"10.1109/IFOST.2011.6021183\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Coal mining gas emission was constrained by many factors. Considering the eight main factors of gas emission, using ant colony clustering and fuzzy C means clustering applied to data pre-processing, determine the membership function of emission. Fuzzy rules extracted from the data sample, establish a fuzzy neural network prediction system of coal mining gas emission.\",\"PeriodicalId\":20466,\"journal\":{\"name\":\"Proceedings of 2011 6th International Forum on Strategic Technology\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-09-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of 2011 6th International Forum on Strategic Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IFOST.2011.6021183\",\"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 of 2011 6th International Forum on Strategic Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IFOST.2011.6021183","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Prediction of coal mining gas emission based on clustering algorithm and fuzzy neural network
Coal mining gas emission was constrained by many factors. Considering the eight main factors of gas emission, using ant colony clustering and fuzzy C means clustering applied to data pre-processing, determine the membership function of emission. Fuzzy rules extracted from the data sample, establish a fuzzy neural network prediction system of coal mining gas emission.
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