【摘要】 BP神经网络是一种应用面较广的神经网络,但存在明显缺陷:学习收敛速度慢,易陷入局部极小。遗传算法具有良好的搜索全局最优解的能力。在探讨训练样本选取的基础上,耦合遗传算法和BP神经网络构建了遗传网络并应用于砂土液化的评价,通过与动量梯度下降算法改进的BP神经网络对比,表明了基于遗传算法的BP神经网络在砂土液化评价中的优越性。更多还原

【Abstract】 BP neural network has board application,but there are some defects: low efficiency and easy to fall into local minimum.Genetic algorithm possesses the ability of questing for optimum answers.Based on discussing the selection in training data,this paper establishes the genetic network by means of the combination of genetic algorithm and BP neural network,which evaluates sand liquefaction.By contrast of improvement BP neural network using momentum gradient algorithm,it indicates the superiority of BP neural network based on genetic algorithm in the evaluation of sand liquefaction.更多还原