IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v12y2024i4p518-d1335223.html
   My bibliography  Save this article

Associated Probabilities in Insufficient Expert Data Analysis

Author

Listed:
  • Gia Sirbiladze

    (Department of Computer Sciences, Iv. Javakhishvili Tbilisi State University, 0179 Tbilisi, Georgia)

  • Janusz Kacprzyk

    (Intelligent Systems Laboratory, Systems Research Institute, Polish Academy of Sciences, 01-447 Warsaw, Poland)

  • Tinatin Davitashvili

    (Department of Computer Sciences, Iv. Javakhishvili Tbilisi State University, 0179 Tbilisi, Georgia)

  • Bidzina Midodashvili

    (Department of Computer Sciences, Iv. Javakhishvili Tbilisi State University, 0179 Tbilisi, Georgia)

Abstract

Problems of modeling uncertainty and imprecision for the analysis of insufficient expert data (IED) are considered in the environment of interactive multi-group decision-making (MGDM). Based on the Choquet finite integral, a moments’ method for the IED is developed for the evaluation of the associated probabilities class (APC) of Choquet’s second-order capacity based on the informational entropy maximum principle. Based on the IED new approach of the lower and upper Choquet’s second-order capacities, identification is developed. The second pole of insufficient expert data, the data imprecision indicator, is presented in the form of a fuzzy subset and image on the alternatives set. In the environment of the Dempster–Shafer belief structure, connections between an associated possibilities class (APosC), with the APC, and an associated focal probabilities class (AFPC) are constructed. In the approach of A. Kaufman’s theory of expertons, based on the APosC and the AFPC unique fuzzy subset, the IED image on the alternatives set is constructed. Based on Sugeno’s finite integral most typical value (MTV), as a prediction on possible alternatives set, the IED is constructed. In the example, a sensitive and comparative analysis is provided for the evaluation of the new approach’s stability and reliability.

Suggested Citation

  • Gia Sirbiladze & Janusz Kacprzyk & Tinatin Davitashvili & Bidzina Midodashvili, 2024. "Associated Probabilities in Insufficient Expert Data Analysis," Mathematics, MDPI, vol. 12(4), pages 1-24, February.
  • Handle: RePEc:gam:jmathe:v:12:y:2024:i:4:p:518-:d:1335223
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/12/4/518/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2227-7390/12/4/518/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Grabisch, Michel & Kojadinovic, Ivan & Meyer, Patrick, 2008. "A review of methods for capacity identification in Choquet integral based multi-attribute utility theory: Applications of the Kappalab R package," European Journal of Operational Research, Elsevier, vol. 186(2), pages 766-785, April.
    2. Merigó, José M. & Casanovas, Montserrat & Yang, Jian-Bo, 2014. "Group decision making with expertons and uncertain generalized probabilistic weighted aggregation operators," European Journal of Operational Research, Elsevier, vol. 235(1), pages 215-224.
    3. Gia Sirbiladze, 2016. "New Fuzzy Aggregation Operators Based on the Finite Choquet Integral — Application in the MADM Problem," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 15(03), pages 517-551, May.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Gia Sirbiladze & Otar Badagadze, 2017. "Intuitionistic Fuzzy Probabilistic Aggregation Operators Based on the Choquet Integral: Application in Multicriteria Decision-Making," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 16(01), pages 245-279, January.
    2. Gia Sirbiladze & Anna Sikharulidze, 2018. "Extensions of Probability Intuitionistic Fuzzy Aggregation Operators in Fuzzy MCDM/MADM," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 17(02), pages 621-655, March.
    3. Gia Sirbiladze, 2016. "New Fuzzy Aggregation Operators Based on the Finite Choquet Integral — Application in the MADM Problem," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 15(03), pages 517-551, May.
    4. Gia Sirbiladze, 2021. "Associated Probabilities in Interactive MADM under Discrimination q-Rung Picture Linguistic Environment," Mathematics, MDPI, vol. 9(18), pages 1-36, September.
    5. Gia Sirbiladze & Teimuraz Manjafarashvili, 2022. "Connections between Campos-Bolanos and Murofushi–Sugeno Representations of a Fuzzy Measure," Mathematics, MDPI, vol. 10(3), pages 1-21, February.
    6. Maryam Eghbal & Farzaneh Nassirzadeh & Davood Askarany, 2024. "The Relationship Between Non-additivity Valuations, Cash Flows and Sales Growth," Computational Economics, Springer;Society for Computational Economics, vol. 64(1), pages 429-459, July.
    7. Paugam, Luc, 2011. "Valorisation et reporting du goodwill : enjeux théoriques et empiriques," Economics Thesis from University Paris Dauphine, Paris Dauphine University, number 123456789/8007 edited by Casta, Jean-François.
    8. Dengsheng Wu & Xiaoqian Zhu & Jie Wan & Chunbing Bao & Jianping Li, 2019. "A Multiobjective Optimization Approach for Selecting Risk Response Strategies of Software Project: From the Perspective of Risk Correlations," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 18(01), pages 339-364, January.
    9. Jean-François Casta & Luc Paugam & Hervé Stolowy, 2011. "Non-additivity in accounting valuation: Internally generated goodwill as an aggregation of interacting assets," Post-Print halshs-00541525, HAL.
    10. Lorenza Campagnolo & Carlo Carraro & Fabio Eboli & Luca Farnia, 2015. "Assessing SDGs: A New Methodology to Measure Sustainability," Working Papers 2015.89, Fondazione Eni Enrico Mattei.
    11. Francesco Sica & Francesco Tajani & Maria Rosaria Guarini & Rossana Ranieri, 2023. "A Sensitivity Index to Perform the Territorial Sustainability in Uncertain Decision-Making Conditions," Land, MDPI, vol. 12(2), pages 1-21, February.
    12. Peter Reichert & Klemens Niederberger & Peter Rey & Urs Helg & Susanne Haertel-Borer, 2019. "The need for unconventional value aggregation techniques: experiences from eliciting stakeholder preferences in environmental management," EURO Journal on Decision Processes, Springer;EURO - The Association of European Operational Research Societies, vol. 7(3), pages 197-219, November.
    13. Gia Sirbiladze & Irina Khutsishvili & Otar Badagadze & Mikheil Kapanadze, 2016. "More Precise Decision-Making Methodology in the Temporalized Body of Evidence. Application in the Information Technology Management," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 15(06), pages 1469-1502, November.
    14. Pingtao Yi & Qiankun Dong & Weiwei Li, 2021. "A family of IOWA operators with reliability measurement under interval-valued group decision-making environment," Group Decision and Negotiation, Springer, vol. 30(3), pages 483-505, June.
    15. Doumpos, Michael & Zopounidis, Constantin, 2011. "Preference disaggregation and statistical learning for multicriteria decision support: A review," European Journal of Operational Research, Elsevier, vol. 209(3), pages 203-214, March.
    16. Mayag, Brice & Bouyssou, Denis, 2020. "Necessary and possible interaction between criteria in a 2-additive Choquet integral model," European Journal of Operational Research, Elsevier, vol. 283(1), pages 308-320.
    17. Ferreira, João J.M. & Jalali, Marjan S. & Ferreira, Fernando A.F., 2018. "Enhancing the decision-making virtuous cycle of ethical banking practices using the Choquet integral," Journal of Business Research, Elsevier, vol. 88(C), pages 492-497.
    18. Angilella, Silvia & Greco, Salvatore & Matarazzo, Benedetto, 2010. "Non-additive robust ordinal regression: A multiple criteria decision model based on the Choquet integral," European Journal of Operational Research, Elsevier, vol. 201(1), pages 277-288, February.
    19. Wu, Xingli & Liao, Huchang, 2023. "A compensatory value function for modeling risk tolerance and criteria interactions in preference disaggregation," Omega, Elsevier, vol. 117(C).
    20. Mikhail Timonin, 2012. "Maximization of the Choquet integral over a convex set and its application to resource allocation problems," Annals of Operations Research, Springer, vol. 196(1), pages 543-579, July.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jmathe:v:12:y:2024:i:4:p:518-:d:1335223. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.