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

机译:优化小波神经网络在基于遗传算法的煤层屋顶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的价值很大。鉴于最新研究,本文根据各种影响因素与强度稳定性之间的复杂非线性映射关系,结果是基于遗传算法的优化小波神经网络的屋顶稳定性预测的GA-Wnn模型。该方法克服了BP算法的一些缺点,例如局部最小和过度拟合。实际仿真结果表明,GA-WNN模型可以有效地提高网络的诊断精度,提高收敛速度。该模型适用于煤屋顶稳定性的估计。

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