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阐述小波神经网络模型法的基本原理与程序实施步骤,探讨了高陡边坡监测数据与小波神经网络间的联系,建立了基于小波神经元网络的高陡边坡预报模型.以工程实例为背景,对高陡边坡位移进行预测预报,并与其它方法对比分析.研究表明:小波神经网络具有较好的函数逼近能力和容错能力,经过选取恰当的网络参数,较少的级数项组成的小波神经网络就能达到良好的预测效果.
The basic principle of wavelet neural network modeling method and the procedure of program implementation are expounded, the connection between monitoring data of high and steep slope and wavelet neural network is discussed, and the prediction model of high and steep slope based on wavelet neural network is established. , Predicts and predicts the displacements of high and steep slope and compares them with other methods.The results show that the wavelet neural network has better function approximation ability and fault tolerance ability.After selecting the appropriate network parameters and fewer series Wavelet neural network can achieve good predictive effect.