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Application of optimized wavelet neural network to the evaluation of coal seam-roof stability based on genetic algorithm

机译:基于遗传算法的优化小波神经网络在煤层顶板稳定性评价中的应用

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Roof stability prediction features randomness, complexity and instability, and precise prediction places much value on theoretical and practical application. In light of the latest research, this paper, according to complicated nonlinear mapping relation between various influence factors and stability of intensity, turns out that the GA-WNN model of roof stability prediction, with optimized wavelet neural network based on genetic algorithm, is constructed. This method overcomes some drawbacks of BP algorithm, such as local minimum and over-fitting. The Practical simulation results show that GA-WNN model can effectively increase the diagnostic accuracy of the network and improve the speed of convergence. This model applies to estimation of coal roof stability.
机译:屋顶稳定性的预测具有随机性,复杂性和不稳定性,精确的预测在理论和实际应用中具有重要的价值。根据最新研究成果,根据各种影响因素与强度稳定性之间复杂的非线性映射关系,得出了基于遗传算法的优化小波神经网络的GA-WNN屋顶稳定性预测模型。 。该方法克服了BP算法的一些缺点,如局部最小值和过度拟合。实际仿真结果表明,GA-WNN模型可以有效提高网络的诊断精度,提高收敛速度。该模型适用于煤顶板稳定性的估算。

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