Knowledge discovery by Compensatory Fuzzy Logic predicates using a metaheuristic approach
Marlies Martínez Alonso, Rafael Espín Andrade
Marlies Martínez Alonso
Available Online October 2013.
- https://doi.org/10.2991/.2013.3How to use a DOI?
- Compensatory Fuzzy Logic, Knowledge Discovery, Metaheuristic algorithms
- 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.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
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 - 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 - https://doi.org/10.2991/.2013.3 ID - MartínezAlonso2013/10 ER -