Knowledge discovery by Compensatory Fuzzy Logic predicates using a metaheuristic approach

DOI

10.2991/.2013.3How to use a DOI?

Keywords

Compensatory Fuzzy Logic, Knowledge Discovery, Metaheuristic algorithms

Abstract

Compensatory Fuzzy Logic (CFL) is a logical system, which enables an optimal way for the modeling of knowledge. Its axiomatic character enables the work of natural language translation of logic, so it is used in knowledge discovery and decision-making. In this work we propose a general and flexible approach for knowledge discovery which allows obtaining different knowledge structure using a metaheuristic approach. The proposed method was tested by experimental analysis from a data set, using a tool developed in visual Prolog. The experimental results show some advantages of the proposed approach for representing patterns and trends from data.

Copyright

© 2013, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Marlies Martínez Alonso
AU  - Rafael Espín Andrade
PY  - 2013/10
DA  - 2013/10
TI  - Knowledge discovery by Compensatory Fuzzy Logic predicates using a metaheuristic approach
BT  - Proceedings of the Fourth International Workshop on Knowledge Discovery, Knowledge Management and Decision Support
PB  - Atlantis Press
SP  - 17
EP  - 26
SN  - 1951-6851
UR  - https://doi.org/10.2991/.2013.3
DO  - 10.2991/.2013.3
ID  - MartínezAlonso2013/10
ER  -