Displaying similar documents to “Using genetic feature selection for optimizing user profiles.”

Multi-stage genetic fuzzy systems based on the iterative rule learning approach.

Antonio González, Francisco Herrera (1997)

Mathware and Soft Computing

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Genetic algorithms (GAs) represent a class of adaptive search techniques inspired by natural evolution mechanisms. The search properties of GAs make them suitable to be used in machine learning processes and for developing fuzzy systems, the so-called genetic fuzzy systems (GFSs). In this contribution, we discuss genetics-based machine learning processes presenting the iterative rule learning approach, and a special kind of GFS, a multi-stage GFS based on the iterative rule learning...

Improvement to the cooperative rules methodology by using the ant colony system algorithm.

Rafael Alcalá, Jorge Casillas, Oscar Cordón, Francisco Herrera (2001)

Mathware and Soft Computing

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The cooperative rules (COR) methodology [2] is based on a combinatorial search of cooperative rules performed over a set of previously generated candidate rule consequents. It obtains accurate models preserving the highest interpretability of the linguistic fuzzy rule-based systems. Once the good behavior of the COR methodology has been proven in previous works, this contribution focuses on developing the process with a novel kind of metaheuristic algorithm: the ant colony system one....

A GA-P algorithm to automatically formulate extended Boolean queries for a fuzzy information retrieval system.

Oscar Cordón, Félix de Moya, Carmen Zarco (2000)

Mathware and Soft Computing

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Although the fuzzy retrieval model constitutes a powerful extension of the Boolean one, being able to deal with the imprecision and subjectivity existing in the Information Retrieval process, users are not usually able to express their query requirements in the form of an extended Boolean query including weights. To solve this problem, different tools to assist the user in the query formulation have been proposed. In this paper, the genetic algorithm-programming technique is considered...

Evolutionary algorithms and fuzzy sets for discovering temporal rules

Stephen G. Matthews, Mario A. Gongora, Adrian A. Hopgood (2013)

International Journal of Applied Mathematics and Computer Science

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A novel method is presented for mining fuzzy association rules that have a temporal pattern. Our proposed method contributes towards discovering temporal patterns that could otherwise be lost from defining the membership functions before the mining process. The novelty of this research lies in exploring the composition of fuzzy and temporal association rules, and using a multi-objective evolutionary algorithm combined with iterative rule learning to mine many rules. Temporal patterns...

A multicriteria genetic tuning for fuzzy logic controllers.

Rafael Alcalá, Jorge Casillas, Juan Luis Castro, Antonio González, Francisco Herrera (2001)

Mathware and Soft Computing

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This paper presents the use of genetic algorithms to develop smartly tuned fuzzy logic controllers in multicriteria complex problems. This tuning approach has some specific restrictions that make it very particular and complex because of the large time requirements existing due to the need of considering multiple criteria -which enlarges the solution search space-, and to the long computation time models usually used for fitness assessment. To solve these restrictions, two efficient...

ReSySTER: A hybrid recommender system for Scrum team roles based on fuzzy and rough sets

Ricardo Colomo-Palacios, Israel González-Carrasco, José Luis López-Cuadrado, Ángel García-Crespo (2012)

International Journal of Applied Mathematics and Computer Science

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Agile development is a crucial issue within software engineering because one of the goals of any project leader is to increase the speed and flexibility in the development of new commercial products. In this sense, project managers must find the best resource configuration for each of the work packages necessary for the management of software development processes in order to keep the team motivated and committed to the project and to improve productivity and quality. This paper presents...

A fuzzy-evolutionary seller agent for an automatic negotiation framework on e-commerce.

Ramón Manjavacas, José Jesús Castro Sánchez, Juan Moreno García (2006)

Mathware and Soft Computing

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The business achievement via e-commerce is getting more important at the present time. E-commerce implies several activities. One of the most significant activity is the consummation of negotiations between sellers and buyers with the aim of reaching agreements. In order to automate these activities the intelligent agent software model is applied. In this work, it is proposed the design of a seller agent for negotiating in competitive frameworks, where many seller agents and a buyer...

The logistic decision making in management accounting with genetic algorithms and fuzzy sets.

Enrique López González, M. Angel Rodríguez-Fernández, Cristina Mendaña-Cuervo (2000)

Mathware and Soft Computing

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The logistics problems in business environments deal with assignation from a number of sources to a number of destinations. Each source offers amounts of goods, while each destination demands quantities of these goods. The object is to find the cheapest transporting schedule that satisfies the demand without violating supply restraints. In this paper we propose to use Fuzzy Sets to represent the previsional information related to costs, demands and other variables. Moreover, we suggest...