Abstract
Normally a decision support system is build to solve problem where multi-criteria decisions are involved. The database is the vital part of the decision support containing the information or data that is used in decision-making process. This is the field where engineers and scientists try to apply several heuristics and soft computing techniques such as learning, search and modelling the imprecise information to obtain optimal decisions. In this paper, we present the proposed a generic framework using evolutionary fuzzy systems to obtain decision rules automatically and the usage of fuzzy inference system to process the imprecise information. Some simulation results demonstrating the difficulties to decide the optimal quantity of membership functions, shape and parameters are also provided.
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Tran, C., Jain, L.C., Abraham, A. (2002). Adaptive Database Learning in Decision Support Systems Using Evolutionary Fuzzy Systems: A Generic Framework. In: Abraham, A., Köppen, M. (eds) Hybrid Information Systems. Advances in Soft Computing, vol 14. Physica, Heidelberg. https://doi.org/10.1007/978-3-7908-1782-9_18
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DOI: https://doi.org/10.1007/978-3-7908-1782-9_18
Publisher Name: Physica, Heidelberg
Print ISBN: 978-3-7908-1480-4
Online ISBN: 978-3-7908-1782-9
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