Choquet integral-based measures of economic welfare and species diversity

被引:8
|
作者
Beliakov, Gleb [1 ]
James, Simon [1 ]
机构
[1] Deakin Univ, Sch Informat Technol, Geelong, Vic, Australia
基金
澳大利亚研究理事会;
关键词
buoyancy; Choquet integral; economic welfare; fuzzy measure; optimisation; Pigou-Dalton principle; AGGREGATION FUNCTIONS; INEQUALITY; DECOMPOSITION; OPTIMIZATION; INDEXES;
D O I
10.1002/int.22609
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Measures of diversity, spread and inequality can be important indicators in domains as diverse as ecology, economics and health. One of the key characteristics of such indices is the Pigou-Dalton (P-D) principle, also known as the principle of progressive transfers, whereby proportional redistribution from larger to smaller arguments should increase (or decrease, depending on the context) the overall measure of social or economic welfare, diversity and so on. Previous studies have identified the ordered weighted averaging operators as being appropriate for welfare measurement, subject to conditions on the weighting vectors. We propose the Choquet integral, defined with respect to a capacity or fuzzy measure, as a candidate for defining nonsymmetric measures of welfare. This allows for importance and interaction to be modelled between inputs while still satisfying the P-D principle. We extend the buoyancy concept to fuzzy measures and characterise the resulting classes of buoyant and antibuoyant fuzzy measures. We then turn to the problem of optimisation of the Choquet integral subject to linear constraints, which in the case of antibuoyant fuzzy measures permits an efficient linear programming solution.
引用
收藏
页码:2849 / 2867
页数:19
相关论文
共 50 条
  • [1] Choquet integral-based morphological operators
    Hocaoglu, AK
    Gader, P
    NONLINEAR IMAGE PROCESSING X, 1999, 3646 : 46 - 55
  • [2] Choquet fuzzy integral-based identification
    Srivastava, S
    Singh, M
    Hanmandlu, M
    2004 IEEE CONFERENCE ON CYBERNETICS AND INTELLIGENT SYSTEMS, VOLS 1 AND 2, 2004, : 1335 - 1340
  • [3] Toward accurate Choquet integral-based neural network
    Yue, SH
    Wang, ZY
    Proceedings of 2005 International Conference on Machine Learning and Cybernetics, Vols 1-9, 2005, : 4621 - 4624
  • [4] Attitudinal Choquet Integral-Based Stochastic Multicriteria Acceptability Analysis
    Mi, Xiaomei
    Liao, Huchang
    Zeng, Xiao-Jun
    2020 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN), 2020,
  • [5] Choquet integral-based intuitionistic fuzzy bonferroni mean operator
    Garg, Harish
    Agarwal, Nikunj
    Tripathi, Alka
    2016 NINTH INTERNATIONAL CONFERENCE ON CONTEMPORARY COMPUTING (IC3), 2016, : 397 - 400
  • [6] Choquet integral-based decision making approach for robot selection
    Karsak, EE
    KNOWLEDGE-BASED INTELLIGENT INFORMATION AND ENGINEERING SYSTEMS, PT 2, PROCEEDINGS, 2005, 3682 : 635 - 641
  • [7] Choquet fuzzy integral-based hierarchical networks for decision analysis
    Chiang, JH
    IEEE TRANSACTIONS ON FUZZY SYSTEMS, 1999, 7 (01) : 63 - 71
  • [8] Choquet integral-based aggregation of image template matching algorithms
    Kim, SH
    Tizhoosh, HR
    Kamel, M
    NAFIPS'2003: 22ND INTERNATIONAL CONFERENCE OF THE NORTH AMERICAN FUZZY INFORMATION PROCESSING SOCIETY - NAFIPS PROCEEDINGS, 2003, : 143 - 148
  • [9] Comments on "Choquet fuzzy integral-based hierarchical networks for decision analysis"
    Hocaoglu, AK
    Gader, P
    IEEE TRANSACTIONS ON FUZZY SYSTEMS, 1999, 7 (06) : 767 - 768
  • [10] Choquet Integral-Based Aggregation for the Analysis of Anomalies Occurrence in Sustainable Transportation Systems
    Karczmarek, Pawel
    Galka, Lukasz
    Kiersztyn, Adam
    Dolecki, Michal
    Kiersztyn, Krystyna
    Pedrycz, Witold
    IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2023, 31 (02) : 536 - 546