不同神经网络在岩体质量分级中的应用与比较

Application and Comparison of Different Neural Network in Rock Mass Quality Classification

在使用统一的学习和测试数据的基础上,通过在MATLAB人工神经网络工具箱中进行模拟计算,比较了BP神经网络、概率神经网络、学习矢量量化神经网络和Elman神经网络在模式分类方面的异同和优劣,分析了这4种神经网络的适用条件,为人工神经网络方法在岩体质量分级中的应用提供了有益的借鉴和参考。

On the basis of using the same training and testing data, through simulating calculation done in MATLAB artificial neural network toolbox, similarities and differences, advantages and disadvan- tages of BP neural network, probabilistic neural network, learning vector quantization neural network and Elman neural network on pattern classification aspect were compared. Applicable conditions of these four kinds of neural network were analyzed. It provides useful reference for artificial neural network method in the application of rock mass quality classification.