Interval number grey target decision-making model based on multi-dimensional association sampling and its application

被引：0
|
作者：
Wang L. [1 ]
Yan X. [1 ]
Wang B. [2 ]
Yu H. [1 ]
Ji C. [1 ]
机构：
[1] School of Renewable Energy, North China Electric Power University, Beijing
[2] Nari Group Corporation Water Resource and Hydropower Technology Company, Nanjing
来源：
Xitong Gongcheng Lilun yu Shijian/System Engineering Theory and Practice | 2019年 / 39卷 / 06期
基金：
中国国家自然科学基金;
关键词：
Interval number grey target model; Multi-dimensional association sampling; Reservoir operation; Risk assessment; Set-valued statistic;
D O I：
10.12011/1000-6788-2018-0862-13
中图分类号：
学科分类号：
摘要：
The existing interval number grey target decision-making model ignores the important influence of interval distribution and the correlation between the indicators in scheme evaluation. And there are some fuzzy errors when setting the weight of indicators. In order to solve the above problems, this paper proposes an interval number grey target decision-making model based on multi-dimensional association sampling, taking into account the multi-dimensional joint probability density distribution of index space and its boundary, and weakens the impact of extreme index value on the decision-making results. In addition, this paper determines the weight of index by using set-valued statistical method, expanding the weight of grey target model from the real number sequence to the interval number sequence, and reducing the fuzzy error in the experts' judgment process. This improved model is applied to Pankou reservoir for the decision-making of water level operating in flood season. Compared with traditional models, the improved model fully considers the characteristics of interval data and the correlation between the indicators. Meanwhile, the setting of interval number weight is more scientific and reasonable. © 2019, Editorial Board of Journal of Systems Engineering Society of China. All right reserved.
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页码：1610 / 1622
页数：12
相关论文
共 29 条
  • [1] Xu Z.S., A method based on objective similarity scale for multi-objective decision-making, Systems Engineering Theory & Practice, 21, 9, pp. 101-104, (2001)
  • [2] Guo S., Zhao H.R., Optimal site selection of electric vehicle charging station by using fuzzy TOPSIS based on sustainability perspective, Applied Energy, 158, pp. 390-402, (2015)
  • [3] Tripathy S., Tripathy D.K., Multi-attribute optimization of machining process parameters in powder mixed electro-discharge machining using TOPSIS and grey relational analysis, Engineering Science and Technology, 19, pp. 62-70, (2016)
  • [4] Xiao Y.Q., Wang K.P., He G.J., Et al., Fuzzy comprehensive evaluation for operating condition of large-scale wind turbines based on trend predication, Proceedings of the CSEE, 34, 13, pp. 2132-2139, (2014)
  • [5] Liu J.H., Luo L.F., Zhang Z.W., Et al., comprehensive evaluation of power quality based on fuzzy set pair analysis, Power System Technology, 36, 7, pp. 81-85, (2012)
  • [6] Lan R., Fan J.L., TOPSIS decision-making method on three parameters interval-valued fuzzy sets, Systems Engineering Theory & Practice, 29, 5, pp. 129-136, (2009)
  • [7] Li Y.B., Yu X.Y., Wang Z.J., Risk assessment on photovoltaic power generation project by grey correlation analysis and TOPSIS method, Power System Technology, 37, 6, pp. 1514-1519, (2013)
  • [8] Deng J.L., Grey Theory, (2002)
  • [9] Wang H.Y., Multiple attribute decision making methods for reservior flood control operation, (2010)
  • [10] Ji C.M., Li R.B., Liu D., Et al., Assessment index system and decision-making model for load adjustment schemes of cascade hydropower stations, Journal of Hydraulic Engineering, 48, 3, pp. 261-269, (2017)
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