Soft Computing Applications in Thermal Energy Systems

  • Arturo Pacheco-Vega

Abstract

Soft computing methodologies, of which artificial neural networks (ANNs), genetic algorithms (GAs), fuzzy logic (FL), and cluster analysis (CA) are elements, have gained much attention in recent years as practical tools to analyze complex problems in real-world applications. This chapter presents a review of SC applications in energy systems that belong to the field of thermal engineering. Special attention is devoted to the analysis, design and control of heat exchangers. For each methodology considered, the principles of operation are briefly described and discussed. Various applications to other energy systems are also mentioned.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Arturo Pacheco-Vega
    • 1
  1. 1.California State UniversityLos AngelesUSA

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