Paper Title:
Study on ANFIS Application in Coal Mining Stray Current Security Prediction
  Abstract

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 non-production 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.

  Info
Periodical
Key Engineering Materials (Volumes 426-427)
Edited by
Dunwen Zuo, Hun Guo, Guoxing Tang, Weidong Jin, Chunjie Liu and Chun Su
Pages
216-219
DOI
10.4028/www.scientific.net/KEM.426-427.216
Citation
C.Y. Ma, D.L. Zhang, Z. Wang, G.X. Li, J.J. Tang, "Study on ANFIS Application in Coal Mining Stray Current Security Prediction", Key Engineering Materials, Vols. 426-427, pp. 216-219, 2010
Online since
January 2010
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Price
$32.00
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