Displaying similar documents to “A GA-P algorithm to automatically formulate extended Boolean queries for a fuzzy information retrieval system.”

Using genetic feature selection for optimizing user profiles.

Henrik Legind Larsen, Nicolás Marín, María José Martín-Bautista, M. Amparo Vila (2000)

Mathware and Soft Computing

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Most of the techniques used in text classification are determined by the occurrences of the words (terms) appearing in the documents, combined with the user feedback over the documents retrieved. However, in our model, the most relevant terms will be selected from a previous fuzzy classification given by the genetic algorithm guided by the user feedback, but using techniques from Machine Learning. A feature selection process is carried out through a Genetic Algorithm in order to find...

The use of fuzzy connectives to design real-coded genetic algorithms.

Francisco Herrera, Manuel Lozano, José Luis Verdegay (1994)

Mathware and Soft Computing

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Genetic algorithms are adaptive methods that use principles inspired by natural population genetics to evolve solutions to search and optimization problems. Genetic algorithms process a population of search space solutions with three operations: selection, crossover and mutation. A great problem in the use of genetic algorithms is premature convergence; the search becomes trapped in a local optimum before the global optimum is found. Fuzzy logic techniques may be used for solving this...

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...

A novel fuzzy c-regression model algorithm using a new error measure and particle swarm optimization

Moêz Soltani, Abdelkader Chaari, Fayçal Ben Hmida (2012)

International Journal of Applied Mathematics and Computer Science

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This paper presents a new algorithm for fuzzy c-regression model clustering. The proposed methodology is based on adding a second regularization term in the objective function of a Fuzzy C-Regression Model (FCRM) clustering algorithm in order to take into account noisy data. In addition, a new error measure is used in the objective function of the FCRM algorithm, replacing the one used in this type of algorithm. Then, particle swarm optimization is employed to finally tune parameters...

An inquiry-based method for Choquet integral-based aggregation of interface usability parameters

Miguel-Ángel Sicilia, Elena García Barriocanal, Tomasa Calvo (2003)

Kybernetika

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The concept of usability of man-machine interfaces is usually judged in terms of a number of aspects or attributes that are known to be subject to some rough correlations, and that are in many cases given different importance, depending on the context of use of the application. In consequence, the automation of judgment processes regarding the overall usability of concrete interfaces requires the design of aggregation operators that are capable of modeling approximate or ill-defined...

Evolutionary design of fuzzy logic controllers using strongly-typed GP.

Enrique Alba, Carlos Cotta, José M. Troya (1999)

Mathware and Soft Computing

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An evolutionary approach to the design of fuzzy logic controllers is presented in this paper. We propose the use of the genetic programming paradigm to evolve fuzzy rule-bases (internally represented as type-constrained syntactic trees). This model has been applied to the cart-centering problem, although it can be readily extended to other problems. The obtained results show that a good parameterization of the algorithm, and an appropriate evaluation function, can lead to near-optimal...

Analyzing the reasoning mechanisms in fuzzy rule based classification systems.

Oscar Cordón, María José del Jesús, Francisco Herrera (1998)

Mathware and Soft Computing

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Fuzzy Rule-Based Systems have been succesfully applied to pattern classification problems. In this type of classification systems, the classical Fuzzy Reasoning Method classifies a new example with the consequent of the rule with the greatest degree of association. By using this reasoning method, we do not consider the information provided by the other rules that are also compatible (have also been fired) with this example. In this paper we analyze this problem and propose...

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....