摘要
针对失效模式和影响分析高度不确定的复杂群体判断环境,提出一种新的区间梯形二型模糊(IT2 TF)群体判断聚合方法。通过深度挖掘数据信息求解信息的集中趋势和波动范围,构建隶属函数参数模型,将含有个体判断不确定性的一组区间判断信息聚合成IT2 TF群体判断结果,从而量化群体判断的一致性意见并记录实际存在的不确定性信息。算例分析结果验证了该聚合方法的有效性及实用性,并表明其能提高群体判断结果的准确度。
According to the highly uncertainty group judgment complexity environment bring by Failure Mode and Effects Analysis( FMEA),this paper proposes an novel Interval Type-2 Trapezoidal Fuzzy( IT2 TF) group judgment aggregation method to compute the centralized tendency and fluctuation range of the membership function through the deep mining data information. Based on it,the IT2 TF membership function parameter model is obtained. The model aggregates a set of interval individual judgment with uncertainty information into IT2 TF group judgment result,thereby quantifies the group judgment consensus as well as the uncertainty information by integration of individual judgment. The practicability and effectiveness of the proposed method is demonstrated by an illustrative example and comparative analysis, and indicates it can improve the accuracy of the gourp judgement result.
出处
《计算机工程》
CAS
CSCD
北大核心
2017年第11期173-181,共9页
Computer Engineering
基金
国家自然科学基金(61364016)
中国博士后科学基金(2014M550473
2015T80990)
云南省应用基础研究计划项目(2014FB136)
关键词
失效模式和影响分析
区间梯形二型模糊
群体判断聚合方法
隶属函数
不确定性
Failure Mode and Effects Analysis(FMEA)
Interval Type-2 Trapezoidal Fuzzy( IT2 TF)
group judgment aggregation method
membership function
uncertainty