自适应模糊神经网络在膨胀土胀缩等级分类中的应用

针对膨胀土胀缩等级分类这一多因素评判问题，在分析自适应模糊神经网络原理及结构的基础上，利用减法聚类获得模糊推理规则数目，确定网络结构，建立了适用于膨胀土分类的自适应模糊神经网络，并将其应用于两个实际工程的膨胀土分类中，取得了良好的效果。研究结果表明，自适应模糊神经网络能实现BP网络和模糊综合评判的分类功能，而且比BP网络具有更透明的网络结构、比模糊综合评判更具学习功能，在膨胀土胀缩等级的分类中显示出较强的适用性。

Application of adaptive-network-based fuzzy inference systems to classification of swelling-shrinkage grade of expansive soils

The expansive potential of expansive soils is decided by many factors.It is a multi-factors evaluation problem for classification of swelling-shrinkage grade of expansive soil.The theory of adaptive-network-based fuzzy inference systems(ANFIS) was introduced and subtractive cluster method was applied to deciding fuzzy inference rules.After that,an ANFIS was proposed and applied to two engineerings.Good results were obtained for many test examples.It is concluded that ANFIS can function as BP neural network and fuzzy comprehensive evaluation on classification of swelling-shrinkage grade of expansive soil;and moreover,ANFIS is clearer than BP neural network in network structure and possesses of self-study ability compared with fuzzy comprehensive evaluation.The application of ANFIS on classification of swelling-shrinkage grade of expansive soil is feasible.