Study on ANFIS Application in Coal Mining Stray Current Security Prediction

摘要：

On basis of analyzing the principles and structure of adaptive neural fuzzy inference system (ANFIS), this thesis used subtractive clustering algorithm to get fuzzy inference rule numbers and confirm the network structure. In addition, the thesis built ANFIS model adapted to coal mining workface stray current security prediction. The model can do workface stray current security prediction by the easy measured parameters of nonproduction field. If the stray current exceeds standard, the system will alarm on time. Moreover, the thesis compared accuracy rate of the security prediction results under different membership functions. The results indicate that the prediction accuracy of ANFIS based on subtractive clustering is the highest and its computing speed is faster. The prediction results to practical project data indicate that stray current security prediction based on ANFIS has favorable practicality and effect.

关键词： ANFIS Stray current Security prediction

作者: C.Y.Ma D.L.Zhang Z.Wang G.X.Li J.J.Tang

作者单位: School of information and electrical engineering,China University of mining and technology,Xuzhou,Jiangsu Province,China,221008

会议类型: 国际会议

会议名称: The 3rd Conference of Cross-Strait Engineering Education and Ceeusro & 1st International Conference on Engineering Technologies and Ceeusro(ICETC2009)(第三届工程技术与产学研研讨会暨第一届国际功能制造技术学术会议)

会议地点: 常州

会议语种:英文

页码: 216-219

在线出版日期: 2009-11-19（万方平台首次上网日期，不代表论文的发表时间）