Probability estimation based on grey system theory for simulation evaluation

作     者：Jianmin Wang Jinbo Wang Tao Zhang Yunjie Wu 

作者机构：Technology and Engineering Center for Space Utilization Chinese Academy of Sciences School of Automation Science and Electrical Engineering Beihang University 

出 版 物：《Journal of Systems Engineering and Electronics》 (系统工程与电子技术（英文版）)

年 卷 期：2016年第27卷第4期

页      面：871-877页

核心收录：

学科分类：0711[理学-系统科学] 02[经济学] 0202[经济学-应用经济学] 020208[经济学-统计学] 07[理学] 0714[理学-统计学（可授理学、经济学学位）] 070103[理学-概率论与数理统计] 071101[理学-系统理论] 0701[理学-数学] 

主　　题：small sample interval estimation simulation system evaluation probability grey system theory 

摘      要：In the evaluation of some simulation systems, only small samples data are gotten due to the limited conditions. In allusion to the evaluation problem of small sample data, an interval estimation approach with the improved grey confidence degree is *** the basis of the definition of grey distance, three kinds of definition of the grey weight for every sample element in grey estimated value are put forward, and then the improved grey confidence degree is designed. In accordance with the new concept, the grey interval estimation for small sample data is deduced. Furthermore,the bootstrap method is applied for more accurate grey confidence interval. Through resampling of the bootstrap, numerous small samples with the corresponding confidence intervals can be obtained. Then the final confidence interval is calculated from the union of these grey confidence intervals. In the end, the simulation system evaluation using the proposed method is conducted. The simulation results show that the reasonable confidence interval is acquired, which demonstrates the feasibility and effectiveness of the proposed method.