دانلود رایگان ترجمه مقاله روش پژوهش تبدیل درجه عضویت در تصمیم گیری های فازی چند شاخصه (نشریه اسپرینگر 2009)

روش پژوهش تبدیل درجه عضویت در تصمیم گیری های فازی چند شاخصه

The Method Research of Membership Degree Transformation in Multi-indexes Fuzzy Decision-Making

Abstract

The conversion of membership degree is the key computation of fuzzy evaluation for multi-indexes fuzzy decision-making. But the method should be discussed, because redundant data in index membership degree is also used to compute object membership degree, which is not useful for object classification. The new method is: based on data mining of entropy, mining knowledge information about object classification hidden in every index, affirming the relation of object classification and index membership, eliminating the redundant data in index membership for object classification by defining distinguishable weight, extracting valid values to compute object membership. Thus constructing a new membership degree conversion method that can not be effected by redundant data and it is used for fuzzy decision for multi-indexes.

1 Introduction

There are many factors that effect decision goal in relatively decision system, among these effective factors, selecting the more important factors called as indexes; these different indexes are divided into some levels, decision-making index system is a hierarchical structure: the top level contain one factor Q ,called as general goal; base level contains some base levels that are controllable indexes, so every base index (quantitative or qualitative) does not has its index; there are some intermediate levels between top and base level; and except base index, other levels have some index; in order to descript simplify, let hierarchical structure only have one intermediate level, because there is not difference between two intermediate levels or more and one intermediate level by computation.

If the question is simplified, for example, decision-making goal is that determining the importance order of base indexes about top goal (such as simplify plans scheduling). Saaty provides analytic hierarchy process based on“multiple comparison”: under the condition of general goal, scheduling the importance of base indexes, and after the importance of base indexes are normalized, obtaining the importance weights of base indexes of top goal. Although the analytic hierarchy process is not perfect, it can solve above questions scheduling.