{"title":"基于神经网络的铀矿边坡稳定性分析","authors":"Yufeng Zhu, X. Ding, Zhi‐wei Li, Shijian Zhou","doi":"10.1109/IFITA.2010.293","DOIUrl":null,"url":null,"abstract":"How to accurately predict the occurrence of landslides, and it has become one of the troubles in the mining process. The author made a brief introduction of artificial neural network and BP network model in this paper, and also analysis some important problems, such as the parameters selecting, data collecting, processing and network constituting by using the study and forecast samples which from the slope stability of Fuzhou Jin-An Uranium Industry Limited Company, and then setting a prediction model. This paper discusses the slope stability methods and its effectiveness based on the BP neural network. Examples of calculation shows that the using of artificial neural network approaching to the stability of the slope of the forecast can made satisfactory results through the training sample test. This model provides a viable method for the future stability of the slope of such evaluation. At the same time, the feasibility of the application for the neural network in the mine slope stability is proved.","PeriodicalId":393802,"journal":{"name":"2010 International Forum on Information Technology and Applications","volume":"21 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Analysis on Uranic Slope Stability Based on Neural Network\",\"authors\":\"Yufeng Zhu, X. Ding, Zhi‐wei Li, Shijian Zhou\",\"doi\":\"10.1109/IFITA.2010.293\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"How to accurately predict the occurrence of landslides, and it has become one of the troubles in the mining process. The author made a brief introduction of artificial neural network and BP network model in this paper, and also analysis some important problems, such as the parameters selecting, data collecting, processing and network constituting by using the study and forecast samples which from the slope stability of Fuzhou Jin-An Uranium Industry Limited Company, and then setting a prediction model. This paper discusses the slope stability methods and its effectiveness based on the BP neural network. Examples of calculation shows that the using of artificial neural network approaching to the stability of the slope of the forecast can made satisfactory results through the training sample test. This model provides a viable method for the future stability of the slope of such evaluation. At the same time, the feasibility of the application for the neural network in the mine slope stability is proved.\",\"PeriodicalId\":393802,\"journal\":{\"name\":\"2010 International Forum on Information Technology and Applications\",\"volume\":\"21 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-07-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 International Forum on Information Technology and Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IFITA.2010.293\",\"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 International Forum on Information Technology and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IFITA.2010.293","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Analysis on Uranic Slope Stability Based on Neural Network
How to accurately predict the occurrence of landslides, and it has become one of the troubles in the mining process. The author made a brief introduction of artificial neural network and BP network model in this paper, and also analysis some important problems, such as the parameters selecting, data collecting, processing and network constituting by using the study and forecast samples which from the slope stability of Fuzhou Jin-An Uranium Industry Limited Company, and then setting a prediction model. This paper discusses the slope stability methods and its effectiveness based on the BP neural network. Examples of calculation shows that the using of artificial neural network approaching to the stability of the slope of the forecast can made satisfactory results through the training sample test. This model provides a viable method for the future stability of the slope of such evaluation. At the same time, the feasibility of the application for the neural network in the mine slope stability is proved.