Fuzzy evaluation on mining investment decision based on membership degree transformation new algorithm — M(1,2,3)

Abstract

Mining investment is a kind of venture capital, the risk level of which is impacted by various factors. There are still a lot of uncertainty and ambiguity in the process of evaluating on mining investment decision, so it is more suitable to use fuzzy evaluation methods for it. The core of fuzzy evaluation is membership degree transformation. But the existing transformation methods should be questioned, because redundant data in index membership degree is also used to compute object membership degree, which is not useful for object classification. The new algorithm is: using data mining technology based on entropy to mine knowledge information about object classification hidden in every index, affirm the relationship of object classification and index membership, eliminate the redundant data in index membership for object classification by defining distinguishable weight and extract valid values to compute object membership. The new algorithm of membership degree transformation includes three calculation steps which can be summarized as ldquoeffective, comparison and compositionrdquo, which is denoted as M(1,2,3). The paper applied the new algorithm in fuzzy evaluation on mining investment decision.