基于模糊聚类的我国主要港口物流效率分析

由于我国港口物流效率测评中存在大量模糊、不精确的数据,已有方法无法处理;所以港口物流效率评价往往只针对定性数据进行,而忽略了大量有价值的定量知识。如何有效利用定量指标进行物流效率的评价称为一个难点问题。鉴于此,引入模糊聚类算法,针对我国主要港口物流效率中的定量数据进行分析,选取公认的10个物流效率指标,建立了模糊相似关系矩阵;通过进行矩阵元素的合成得到模糊等价关系;并以此得到最终的有效范围及划分结果。最后,通过以我国八大主要港口的指标数据为例,采用模糊聚类进行聚类,结果显示模糊聚类的精度更高,且分析发现其符合各港口的现状。

Analysis on the logistics efficiency of China ports using fuzzy clustering

A lot of vague and imprecise data exist in evaluation of the port logistics efficiency of our country, and the existing methods can not deal with this data. Port logistics efficiency is evaluated only for qualitative data while ignoring the quantitative valuable knowledge. How to effectively use the quantitative evaluation index of logistics efficiency is a difficult problem. For that reason, the fuzzy clustering algorithm was introduced in this paper to analyze the quantitative data of logistics efficiency of mainly ports in our country. The ten logistics efficiency factors and a fuzzy similar relation matrix were recognized, and the fuzzy equivalence relationship was obtained by synthesizing matrix elements in order to get the effective range and final results of clustering. Finally, we applied the fuzzy clustering into classify the eight major ports of our country, and the results show that the accuracy of the fuzzy clustering is higher and is line with the development of each port.