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自适应神经网络在确定落煤残存瓦斯量中的应用

  • Category : AI-NN-PR
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  • Update : 2012-11-26
  • Size : 59kb
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  • Author :王静
  • About : Nobody
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charged residual coal gas is to determine the volume of mining gas emission rate forecast an important link, which directly affect mining gas emission rate forecast accuracy, and with coal metamorphism, loading coal particle size, the original gas content, exposure time and other factors nonlinear relationship. Artificial neural networks have expressed arbitrary nonlinear relationships and the ability to solve complex nonlinear, time-varying uncertainty and the new ideas and new approaches. Based on this, the author of adaptive neural network loading coal residual gas production forecast model, and a combination of different loading coal mine gas remnants of the actual test results of research. Results show that the adaptive value of the right to change step BP neural network model predict
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自适应神经网络在确定落煤残存瓦斯量中的应用.CAJ
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