基于隶属度转换算法的矿业投资决策模糊评价

矿业投资是一种风险投资,评价过程中存在很多不确定性和模糊性。采用基于熵的数据挖掘方法,通过挖掘隐藏在各指标隶属度中关于目标分类的知识信息,厘清目标分类与指标隶属度之间的关系,通过定义指标区分权清除指标隶属度中对目标分类的冗余值,提取有效值计算目标隶属度。新的隶属度转换算法经过"一有效、二可比、三合成"三个计算步骤,简记为M(1,2,3),由此构建隶属度转换新算法并用于矿业投资决策模糊评价中。实例分析表明,判定结果较为理想,具有较高的置信度。

Fuzzy evaluation on mining investment decision based on membership degree transformation algorithm

As mining investment is a kind of venture capital,there are a lot of uncertainty and ambiguity in the process of evaluating on mining investment decision.With the data mining technology,the relationship of object classification and index membership is affirmed based on the entropy to mine knowledge information about object classification hidden in every index.The redundant data in index membership for object classification is eliminated by defining distinguishable weight and extracting valid values to compute object membership.The new algorithm of membership degree transformation consists of three calculation steps which could be summarized as "effective,comparison and composition",and denoted into M(1,2,3).The new algorithm is applied in fuzzy evaluation on mining investment decision,and the case study indicates that this method is characterized by practicability and high confidence for application.