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Solving Electrical Distribution Problems Using Hybrid Evolutionary Data Analysis Techniques

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Abstract

Real-world electrical engineering problems can take advantage of the last Data Analysis methodologies. In this paper we will show that Genetic Fuzzy Rule-Based Systems and Genetic Programming techniques are good choices for tackling with some practical modeling problems. We claim that both evolutionary processes may produce good numerical results while providing us with a model that can be interpreted by a human being. We will analyze in detail the characteristics of these two methods and we will compare them to the some of the most popular classical statistical modeling methods and neural networks.

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Authors and Affiliations

  1. Department of Computer Science and Artificial Intelligence, University of Granada, 18071, Granada, Spain

    Oscar Cordón & Francisco Herrera

  2. Department of Computer Science, University of Oviedo, Oviedo, Spain

    Luciano Sánchez

Authors
  1. Oscar Cordón
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  2. Francisco Herrera
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  3. Luciano Sánchez
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Cordón, O., Herrera, F. & Sánchez, L. Solving Electrical Distribution Problems Using Hybrid Evolutionary Data Analysis Techniques. Applied Intelligence 10, 5–24 (1999). https://doi.org/10.1023/A:1008384630089

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