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A STUDY ON NEURAL NETWORK ON ROCK BLASTABILITY

Feng Xiating(Northea stern University,shenyang 110006)  
With the application of artificial neural network theory and machine learn-ing method,this paper establishes a nonlinear mapping between the blastability of rockand its affected factors such as volume of explosion crater,mass ratio of big rockblocks,ratio of small rock blocks,qualified ratio of blasting and wave impedence andrepresents them distributedly on neural network, connection weights and threshold ofnodes.The blastability of new type of rock mass is predicted by means of the method ofparallel inference.The results show that the proposed method has some more importantad vantag es than traditional ones and it has strong ability for nonlinear dynam ic processing.
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