Displaying similar documents to “A hybrid evolutionary approach to intelligent system design.”

A formal analysis of the computational dynamics in GIGANTEC.

Amr Badr (2001)

Mathware and Soft Computing

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An evolutionary algorithm formalism has been forwarded in a previous research, and implemented in the system GIGANTEC: enetic nduction for eneral nalytical on-numeric ask volution ompiler [Bad98][Bad99]. A dynamical model is developed to analyze the behaviour of the algorithm. The model is dependent in its analysis on classical Compilers Theory, Game Theory and Markov Chains and its convergence characteristics. The results conclude that a limiting state is reached, which is independent...

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...

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...

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....

Advances in parallel heterogeneous genetic algorithms for continuous optimization

Enrique Alba, Francisco Luna, Antonio Nebro (2004)

International Journal of Applied Mathematics and Computer Science

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In this paper we address an extension of a very efficient genetic algorithm (GA) known as Hy3, a physical parallelization of the gradual distributed real-coded GA (GD-RCGA). This search model relies on a set of eight subpopulations residing in a cube topology having two faces for promoting exploration and exploitation. The resulting technique has been shown to yield very accurate results in continuous optimization by using crossover operators tuned to explore and exploit the solutions...

Self-adaptation of parameters in a learning classifier system ensemble machine

Maciej Troć, Olgierd Unold (2010)

International Journal of Applied Mathematics and Computer Science

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Self-adaptation is a key feature of evolutionary algorithms (EAs). Although EAs have been used successfully to solve a wide variety of problems, the performance of this technique depends heavily on the selection of the EA parameters. Moreover, the process of setting such parameters is considered a time-consuming task. Several research works have tried to deal with this problem; however, the construction of algorithms letting the parameters adapt themselves to the problem is a critical...

Fast prototyping of computing-oriented fuzzy-logic systems.

José Ignacio Martínez-Torre, Jean-Pierre Deschamps, Milagros Fernández Centeno (1999)

Mathware and Soft Computing

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In this paper we propose to explore different dedicated hardware solutions in terms of area-speed trade-offs for computing-oriented fuzzy logic systems in the algorithmic abstraction level that fulfil the application requirements applying high level synthesis techniques. The main benefits of this proposal are the capability of selecting the best implementation for any application not being tied down to a predefined architecture, the use of the required number of hardware units and the...

Egipsys: An enhanced gene expression programming approach for symbolic regression problems

Heitor Lopes, Wagner Weinert (2004)

International Journal of Applied Mathematics and Computer Science

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This paper reports a system based on the recently proposed evolutionary paradigm of gene expression programming (GEP). This enhanced system, called EGIPSYS, has features specially suited to deal with symbolic regression problems. Amongst the new features implemented in EGIPSYS are: new selection methods, chromosomes of variable length, a new approach to manipulating constants, new genetic operators and an adaptable fitness function. All the proposed improvements were tested separately,...

A mixed-signal architecture for high complexity CMOS fuzzy controlers.

Rafael Navas-González, Fernando Vidal-Verdú, Angel Rodríguez-Vázquez (1999)

Mathware and Soft Computing

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Analog circuits provide better area/power efficiency than their digital counterparts for low-medium precision requirements [1]. This limit in precision, as well as the lack of design tools when compared to the digital approach, imposes a limit of complexity, hence fuzzy analog controllers are usually oriented to fast low-power systems with low-medium complexity. This paper presents a strategy to preserve most of the advantages of an analog implementation, while allowing a notorious increment...