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Mine Forecast Based on Genetic Annealing Neural Network

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2 Author(s)
Yuxiang Shao ; Sch. of Comput. Sci. & Technol., China Univ. of Geosci., Wuhan, China ; Dongmei Zhang

Since the BP neural network algorithm has some unavoidable disadvantages, such as slowly converging speed and easily running into local infinitesimal, the genetic algorithm and simulated annealing algorithm with the overall search capability has been put forward to optimize authority value and threshold value of BP nerve network. In this paper, GA-SA neural network algorithm model has been established and applied into the mine forecast. The result shows that this model has significant advantages inspect of fast convergence speed, good generalization ability and not easy to yield minimal local results. In generally, this model exhibits good representation and strong prediction ability, and is a helpful tool in the future mine prediction.

Published in:

Information Technology and Computer Science, 2009. ITCS 2009. International Conference on  (Volume:1 )

Date of Conference:

25-26 July 2009

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