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Application Research of a Forecasting Model Based on Wavelet Neural Network

机译:基于小波神经网络的预测模型的应用研究

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A forecasting model for gas emission based on wavelet neural network is proposed in this paper. In the model, wavelet neutral network (WNN) is applied to the forecasting with gradient descent and amended by validity of iteration training algorithm. Compared with back-propagation neural networks, forecasting of the model has advantages of faster convergence and more accurate. Simulation results have proved that the method is valid and feasible.
机译:提出了一种基于小波神经网络的瓦斯涌出量预测模型。该模型将小波神经网络(WNN)应用于梯度下降的预测,并通过迭代训练算法的有效性进行了修正。与反向传播神经网络相比,该模型的预测具有收敛速度更快,准确性更高的优点。仿真结果证明了该方法的有效性和可行性。

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