摘要
针对基于传统模糊综合评判的仿真可信度评估过程中专家根据个人偏好或期望确定权重、模糊合成运算选择不合理等引起的评估结果不准确等问题,提出了一种基于改进模糊综合评判的仿真可信度评估方法。针对树型评估指标体系,利用模糊综合评判矩阵,基于最小隶属度加权平均偏差确定评估指标体系中各层指标的权重;在模糊合成运算环节,利用隶属度加权平均偏差,获取综合评价向量,进而得到仿真可信度评估结果;应用于某半实物仿真系统可信度评估中,计算结果验证了该方法的合理性和可行性。
Aiming at the problems of inaccurate evaluation results caused by experts in the process of simulation credibility evaluation based on traditional fuzzy comprehensive evaluation according to personal preferences or expectations, and unreasonable selection of fuzzy synthetic calculations, a simulation credibility evaluation method based on improved fuzzy comprehensive evaluation is proposed. For the tree-like assessment index system, the fuzzy comprehensive evaluation matrix is used to determine the weight of each index in the assessment index system based on the minimum membership weighted average deviation;in the fuzzy synthesis operation, the membership evaluation weighted average deviation is used to obtain the comprehensive evaluation vector, and then the simulation credibility evaluation result is obtained;it is applied to the credibility assessment of a hardware-in-the-loop simulation system, and the calculation results verify the rationality and feasibility of the method.
作者
冉培志
李伟
鲍然
马萍
Ran Peizhi;Li Wei;Bao Ran;Ma Ping(Control and Simulation Center,Harbin Institute of Technology,Harbin 150001,China;Shanghai Institute of Mechanical and Electrical Engineering,Shanghai 201109,China)
出处
《系统仿真学报》
CAS
CSCD
北大核心
2020年第12期2469-2474,共6页
Journal of System Simulation
基金
国家重点研发计划(2018YFB1701600)。
关键词
可信度评估
模糊综合评判
最小隶属度加权平均偏差
树型评估指标体系
credibility assessment
fuzzy comprehensive evaluation
weighted average deviation of minimum membership degree
tree-like assessment index system