南京大学学报(自然科学版) ›› 2023, Vol. 59 ›› Issue (4): 600–609.doi: 10.13232/j.cnki.jnju.2023.04.007

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基于区间二型模糊多粒度证据融合方法的钢铁行业耗能决策

王冰洁1, 张超1,2(), 李德玉1,2, 马瑾男3, 王渊3   

  1. 1.山西大学计算机与信息技术学院，太原，030006
    2.计算智能与中文信息处理教育部重点实验室，山西大学，太原，030006
    3.山西省信息产业技术研究院有限公司，太原，030012
  • 收稿日期:2023-06-13 出版日期:2023-07-31 发布日期:2023-08-18
  • 通讯作者: 张超 E-mail:czhang@sxu.edu.cn
  • 基金资助:
    国家自然科学基金(62272284);山西省科技创新青年人才团队项目(202204051001015);山西省筹资金资助回国留学人员科研项目(2022?007);山西省高等学校青年科研人员培育计划，山西省高等学校优秀成果培育项目(2019SK036);2023年度山西省研究生教育创新项目“基于大群体多粒度证据融合的钢铁行业耗能评估方法研究”(2023KY137)

Energy consumption decision⁃making of steel industry based on the interval type⁃2 fuzzy multi⁃granularity evidence fusion method

Bingjie Wang1, Chao Zhang1,2(), Deyu Li1,2, Jinnan Ma3, Yuan Wang3   

  1. 1.School of Computer and Information Technology，Shanxi University，Taiyuan，030006，China
    2.Key Laboratory of Computational Intelligence and Chinese Information Processing of Ministry of Education，Shanxi University，Taiyuan，030006，China
    3.Shanxi Information Industry Technology Research Institute Co. , Ltd，Taiyuan，030012，China
  • Received:2023-06-13 Online:2023-07-31 Published:2023-08-18
  • Contact: Chao Zhang E-mail:czhang@sxu.edu.cn

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摘要：

为了探索区间二型模糊背景下的多属性群决策方法，以多粒度概率粗糙集为基础，结合MULTIMOORA（Multi?Objective Optimization by Ratio Analysis Plus the Full Multi?Plicative Form）与证据融合理论，发展了一种基于区间二型模糊信息的多粒度证据融合决策模型.首先，提出多粒度区间二型模糊概率粗糙集模型；然后，通过离差最大化法和熵权法计算决策者权重和属性权重，依据多粒度概率粗糙集和MULTIMOORA法建立区间二型模糊多属性群决策模型，通过源自D?S证据理论的证据融合方法融合得出决策结果.通过钢铁行业耗能的实例，证明提出方法的可行性与有效性，总体上，提出的决策模型具备一定的容错力，有助于获得强解释力的稳健型决策结果.

关键词: 多粒度粗糙集, 概率粗糙集, 证据融合, 区间二型模糊集, 耗能决策

Abstract:

In order to explore multi?attribute group decision?making methods in the background of interval type?2 fuzziness，the paper starts with multigranulation probabilistic rough sets and develops a multi?granularity evidence fusion decision?making model based on interval type?2 fuzzy information via with MULTIMOORA (Multi?Objective Optimization by Ratio Analysis Plus the Full Multi?Plicative Form) method and the evidence fusion theory. First，a multi?granularity interval type?2 fuzzy probabilistic rough set model is put forward. Then，the decision?maker weight and the attribute weight are calculated by the dispersion maximization method and the entropy weight method. Furthermore，in light of multigranulation probabilistic rough sets and the MULTIMOORA method，an interval type?2 fuzzy multi?attribute group decision?making model is established. The decision results are eventually acquired via the evidence fusion method from the D?S evidence theory. At last，the feasibility and effectiveness of the proposed method are verified by a case of energy consumption in steel industry. All in all，the established decision?making model in the paper owns a certain degree of fault tolerance and is conducive to acquiring stable decision results with strong interpretability.

Key words: multigranulation rough set, probabilistic rough set, evidence fusion, interval type?2 fuzzy set, energy consuming decision?making

中图分类号: 

  • TP391

表1

归一化值转换的语言体系"

归一化数值语言体系
0.0Very Low (VL)
0.0,0.103896Low (L)
0.103896,0.292208Medium Low (ML)
0.292208,0.5Medium (M)
0.5,70.707792Medium High (MH)
0.707792,0.896104High (H)
0.896104,1Very High (VH)

表2

语言体系转换的区间二型模糊集"

语言体系区间二型模糊集
VL0,0,0,0.1;1,1,0,0,0,0.05;0.9,0.9
L0,0.1,0.1,0.3;1,1,0.05,0.1,0.1,0.2;0.9,0.9
ML0.1,0.3,0.3,0.5;1,1,0.2,0.3,0.3,0.4;0.9,0.9
M0.3,0.5,0.5,0.7;1,1,0.4,0.5,0.5,0.6;0.9,0.9
MH0.5,0.7,0.7,0.9;1,1,0.6,0.7,0.7,0.8;0.9,0.9
H0.7,0.9,0.9,1;1,1,0.8,0.9,0.9,0.95;0.9,0.9
VH0.9,1,1,1;1,1,0.95,1,1,1;0.9,0.9

图1

区间二型模糊决策算法流程图"

图2

MULTIMOORA方法1的计算结果"

图3

MULTIMOORA方法2的计算结果"

图4

MULTIMOORA方法3的计算结果"

图5

本文方法的最终评价值"

图6

不同g值的图排序结果"

表3

不同g值的表排序结果"

排序结果
g=2x1≻x10≻x13≻x14≻x7≻x6≻x15≻x3≻x9≻x11≻x2≻x4≻x5≻x12≻x8
g=3x1≻x10≻x13≻x14≻x7≻x6≻x15≻x3≻x9≻x11≻x2≻x4≻x5≻x12≻x8
g=4x1≻x10≻x13≻x14≻x7≻x6≻x15≻x3≻x9≻x11≻x2≻x4≻x5≻x12≻x8

图7

本文方法与TOPSIS的对比结果"

图8

本文方法与VIKOR的对比结果"

图9

本文方法与D?S证据理论的对比结果"

图10

本文方法与MULTIMOORA?TOPSIS的对比结果"

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