Abstract
The parameters of main fans in coal mine such as air flow, wind speed, gas concentration and other conditions are closely related, for its complexity, it’s difficult to establish the nonlinear mathematic model, and it’s hard to describe the model properties by traditional identification method. Neural network is used in mine ventilator model identification. BP-Neural network based on L-M algorithm and RBF-Neural network based on K-mean algorithm are used in Neural network. The simulation results show that the two methods can satisfy the needs of identification precision, convergence rate, stability and tracking ability simultaneous.
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Du, X., An, R., Chen, Z. (2011). Model Identification of Coal Main Fans in Mine Based on Neural Network. In: Deng, H., Miao, D., Lei, J., Wang, F.L. (eds) Artificial Intelligence and Computational Intelligence. AICI 2011. Lecture Notes in Computer Science(), vol 7004. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23896-3_21
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DOI: https://doi.org/10.1007/978-3-642-23896-3_21
Publisher Name: Springer, Berlin, Heidelberg
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