Proceedings of the Fourth International Workshop on Knowledge Discovery, Knowledge Management and Decision Support

Session: Fuzzy Logic and Rough Sets for Knowledge Discovery, Knowledge Management and Decision Support

12 articles
Proceedings Article

Multivalued Fuzzy Logics: A Sensitive Analysis

Pablo Michel Marin Ortega, Rafael Espín Andrade, Jorge Marx Gómez
The main goal of this research is develop a sensitive analysis (SA) among some fuzzy operators, to ask the question: which is the most robustness fuzzy operators The fuzzy operators consider in this study are: Zadeh operators, Probabilistic operators and finally the compensatory fuzzy logic operators:...
Proceedings Article

Linguistic Interpretation of Mathematical Morphology

Agustina Bouchet, Gustavo Meschino, Marcel Brun, Rafael Espín Andrade, Virginia Ballarin
Mathematical Morphology is a theory based on geometry, algebra, topology and set theory, with strong application to digital image processing. This theory is characterized by two basic operators: dilation and erosion. In this work we redefine these operators based on compensatory fuzzy logic using a linguistic...
Proceedings Article

Knowledge discovery by Compensatory Fuzzy Logic predicates using a metaheuristic approach

Marlies Martínez Alonso, Rafael Espín Andrade
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...
Proceedings Article

Learning of Fuzzy Cognitive Maps for simulation and knowledge discovery

Gonzalo Napoles, Isel Grau, Ricardo Pérez-García, Rafael Bello
In recent years Fuzzy Cognitive Maps (FCM) has be-come a useful Soft Computing technique for modeling and simulation. They are connectionist and recurrent structures involving concepts describing the system be-havior, and causal connections. This paper describes two abstract models based on Swarm Intelligence...
Proceedings Article

Fuzzy Clustering Approach for Non-cooperative Behavior Detection in Consensus Reaching Processes

Ivan Palomares, Luis Martínez, Francisco Herrera
Consensus reaching processes in group decision making attempt to reach a mutual agreement amongst experts before making a common decision. Classical consensus models are focused on problems where few decision makers participate. However, new societal and technological trends may require a large number...
Proceedings Article

Discovery of fuzzy predicates in database

Taymi Ceruto Cordovés, Orenia Lapeira Mena, Alejandro Rosete Suárez, Rafael Espín Andrade
Advanced technologies have enabled us to collect large amounts of data. These data may be transformed into use-ful knowledge. Because of our limited ability to manually process the data, it is necessary to use automatic tools to mine useful knowledge. Many data-mining methods have been proposed which...
Proceedings Article

Rationality of two fuzzy negotiation solutions by Knowledge Engineering to n-person cooperative games

Erick González, Rafael A. Espín, Gustavo Mazcorro, Salvador Muñoz
The aim of this paper is to prove the rationality of two new fuzzy solutions to cooperative n-person games. They are the Fuzzy Negotiation Solution by Knowledge Engineering and Compensatory Negotiation Solution by Knowledge Engineering, which are based on bargaining over statements coming from experts....
Proceedings Article

Existence and uniqueness of two fuzzy solutions to cooperative games

Erick González, Rafael A. Espín, Gustavo Mazcorro, Rafael Espín
(FNSKE) and Compensatory Negotiation Solution by Knowledge Engineering (CNSKE) are two new solution concepts to n-person cooperative games. They involve a quantitative index, called Good Deal Index (GDI), which is the matrix solution of a recurrent equation. The existence and uniqueness of the GDI entail...
Proceedings Article

Fuzzy constraints in the Truck and Trailer Routing Problem

Isis Torres, Alejandro Rosete, Carlos Cruz, José Luis Verdegay
Techniques based on Soft Computing are useful to solve real-world problems where decision makers use subjective knowledge when making decisions. In many problems in transport and logistics it is necessary to take into account that the available knowledge about the problem is imprecise or uncertain. Truck...
Proceedings Article

Incorporation of Fuzzy Logic to the Black-Scholes Model in Exchange Option Pricing

Manuel Muñoz Palma, Ezequiel Avilés Ochoa
Since the introduction of the uncertainty theory, a new paradigm in economy and finance is formed with the in-corporation of new models that allow a greater degree of accuracy to the reality of the environment of organiza-tions based on the fuzzy logic theory. This article empha-sizes the importance...
Proceedings Article

Support Rough Sets for decision-making

Yenny Villuendas-Rey, Maria M. Garcia-Lorenzo, Rafael Bello
Case-based reduction is viewed as an important prepro-cessing step for case based decision-making. In this pa-per, is introduced a Support Rough Set model to deal with mixed and incomplete data. The Support Rough Set mod-el is used to reduce the case base by using positive and limit regions of decision....
Proceedings Article

Characterization of neighborhood operators for covering based rough sets, using duality and adjointness

Mauricio Restrepo, Chris Cornelis, Jonatan Gómez
Covering based Rough Sets are an important generalization of Rough Set Theory. Basically, they replace the partition generated from an equivalence relation by a covering. In this context many approximation operators can be defined [16, 26, 27, 28, 34]. In this paper we want to discover relationships...