基于模糊熵的多目标模糊优选模型及其应用

Multi-objective fuzzy optimization model based on fuzzy entropy and its application

利用多目标模糊优选法进行方案优选时 ,对各方案的隶属度越离散 ,则越有利于方案的优选 .为达此目的 ,在文献 [1]相对隶属度及其计算方法的基础上 ,将模糊熵引入到多目标模糊优选模型的建模之中 ,提出了基于模糊熵与加权距优距离、加权距劣距离之和最小的多目标模糊优选模型 ,并将其用于矿山安全监测系统的方案优选 .结果表明 。

By the method of multi objective fuzzy optimum, when plans optimum seeking are carrying out, the more subordinate of every plan is separate, the more plans optimum seeking is benefit. In order to achieve this aims and based on the relative subordinate and its methods of calculation in reference[1], leading fuzzy entropy into establishing models of multi objective fuzzy optimum model. And the least multi objective fuzzy optimum seeking models are put forward base on the distance sum of fuzzy entropy and distance from the best and the worst, and the models are put into use in optimum seeking schemes of safety monitoring system in mine. The results show that the models have more advantages.