信息不完全确定的区域产品模糊区间聚类方法

区域产品分类与选择是区域经济发展中最重要和最基础的工作.在产品选择与分类时,需要确定指标权系数和分类阈值等参数,这在实际应用中是比较困难的.针对这种情况,提出了一种信息不完全确定的区域产品模糊区间聚类方法.该方法构建了指标权系数信息不完全确定的最优模糊区间聚类模型,利用遗传算法和改进的FCM算法联合求解所得优化模型,得到指标权系数、最优聚类中心和最优划分,进而确定各产品所属类别.最后将该方法应用于某区域的产品分类和主导产品的确定中,实例计算说明该方法的可行性和有效性.

A Fuzzy Interval Clustering Approach of Regional Products with Incomplete Certain Information

Regional products classification and select is one of the most important and basic work in the regional economic development.When the products are selected and classified,we have to confirm such parameters as criteria's weights and categorized threshold values.This is a difficult job in practice.Focus on this kind of situation,a fuzzy interval clustering method on classification the regional products with incomplete uncertain information have proposed.This method structures a optimum fuzzy interval clustering model whose criteria's weights' information is incomplete uncertain,then solve the problem by GA and FCM jointly and get the criteria's weights,the optimum cluster center and the optimum partition,and then confirm the affiliation of all products.Finally,apply this method to the sureness of the product classification of a region and leading products,an example is given to show the feasibility and availability of this method.