摘要
文章根据自组织神经网络的基本原理,结合55个边坡实例,应用matlab进行编程,建立了边坡影响因素分类处理的神经网络模型,并运用该模型对不同的边坡进行了分类,分类结果提高了神经网络的边坡指标数据的学习效率,从而证明了自组织神经网络对提高用于预测边坡稳定性神经网络性能的有效性。
According to the basic principle of the self-organizing neural networks, combining the 55 slopes＇ data to be the example, applying the matlab, this paper built up the neural network of the processing model of slope＇s factors classification, and made use of the model to classify different slopes. The result of the classification raised the study efficiency of the neural networks, thus it proved that the self-organizing neural networks is useful for promoting the capability of the neural networks used for predicting the slope stability.
出处
《企业技术开发》
2005年第11期35-36,54,共3页
Technological Development of Enterprise
关键词
自组织神经网络
指标
归类
self-organizing neural networks
factor
classification
