SOFM神经网络在物流中心城市分类评价中的应用

分析了中国各地物流中心规划与建设的发展现状,指出其中可能存在的重复建设问题,提出区域物流规划首先要确定区域内的物流中心城市,而物流中心城市的确定实际上是一个分类评价问题。针对这一问题的本质,引入了自组织特征映射神经网络方法,为了说明该方法的可应用性,简单建立了物流中心城市评价指标体系,并在实际数据样本的基础上,利用自组织特征映射神经网络方法对中国的公路主枢纽城市进行了分类评价。通过对其结果进行分析,证实了该方法能有效地解决这一问题。

Application of SOFM neural network for classification and evaluation of logistics center city

Authors analyze the present situation of logistics center planning and construction in China and point out the potential problem of repeated construction. Based on it, authors put forward that determination of the logistics center city is the first thing for regional logistics plan, which is actually a classified question. Aiming at the essence of this question, authors introduce method of self-organizing feature map neural network.In order to show the application of this method, authors establish a simple index system for evaluating logistics center city and classify cities of highway hub on the basis of practical data specimen. The result demonstrates that SOFM is valid for solving such a problem.