A Fuzzy Entropy-Based Group Consensus Measure for Financial Investments
Author:
Affiliation:
1. Institute of Informatics, University of Szeged, 6720 Szeged, Hungary
2. HUN-REN SZTE Research Group on Artificial Intelligence, 6720 Szeged, Hungary
3. Faculty of Economics, ELTE Eötvös Loránd University, 1088 Budapest, Hungary
Abstract
Funder
Artificial Intelligence National Laboratory
Ministry of Innovation and Technology of Hungary from the National Research, Development, and Innovation Fund
Publisher
MDPI AG
Subject
General Mathematics,Engineering (miscellaneous),Computer Science (miscellaneous)
Link
https://www.mdpi.com/2227-7390/12/1/4/pdf
Reference33 articles.
1. Beliakov, G., James, S., and Calvo, T. (2013, January 24–28). Aggregating fuzzy implications to measure group consensus. Proceedings of the 2013 Joint IFSA World Congress and NAFIPS Annual Meeting (IFSA/NAFIPS), IEEE, Edmonton, AB, Canada.
2. A fuzzy relation space for group decision theory;Bezdek;Fuzzy Sets Syst.,1978
3. Spillman, B., Spillman, R., and Bezdek, J. (1980). Fuzzy Sets: Theory and Applications to Policy Analysis and Information Systems, Springer.
4. Butler, C.L., and Rothstein, A. (1988). On Conflict and Consensus, Food Not Bombs.
5. Consensus reaching in committees;Eklund;Eur. J. Oper. Res.,2007
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