Expert System of Full-Mechanized Face Equipment Fitting Based on Artificial Neural Network

Article Preview

Abstract:

Expert system of full-mechanized face equipment fitting based on artificial neural network is researched and processing method is presented in this paper. On the basis of this, BP neural network models for the forecast of production capability of mining face and the parameters of equipment fitting of full-mechanized mining face are built up. Employing these models forecasts the output, work efficiency and main technical parameters of full-mechanized equipment of the test mining face in Ji'er Colliery.

You might also be interested in these eBooks

Info:

Periodical:

Pages:

1581-1585

Citation:

Online since:

March 2011

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2011 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

[1] Pu Bao-shan, in: Equipment shaping and fitting of the high yield and efficiency mining face for the thin seam mining , new theory of mining engineering[A], Beijing mining institute, graduate proceedings of Beijing mining institute[C] , the Coal Industry Press , (2005).

DOI: 10.47939/et.v3i2.557

Google Scholar

[2] Hu Wan-chang, in: Equipment fitting practice and discussion of the high yield and efficiency full-mechanized mining face[J], Coal Science and Technology , 2002 (1).

Google Scholar

[3] Fan Shao-gang, YaoJian-guo, and Fan Yun-ce, in: Equipment fitting and process design of 6 million t full-mechanized caving mining face[J], Journal of China Coal Society , 2002 (26).

Google Scholar

[4] Yv Shu-wei, in: Improved BP neural network of the fully-mechanized mining face of productive target forecast[J], Journal of China Coal Society, 1999, 24 (2): 22-26.

Google Scholar