Artificial Intelligence in Renewable Energy Applications in Buildings
Date Issued
July 2005
Author(s)
Abstract
Artificial intelligence (AI) systems comprise three major areas, artificial neural networks (ANNs),
genetic algorithms (GA) and fuzzy logic. The major objective of this paper is to illustrate how artificial
intelligence techniques might play an important role in modelling and prediction of the performance of
renewable energy systems in buildings. The paper outlines an understanding of how neural networks, genetic
algorithms and fuzzy systems operate by way of presenting a number of problems in the different disciplines of
renewable energy applications in buildings. The various applications are presented in a thematic rather than a
chronological or any other order. Results presented in this paper, are testimony to the potential of artificial
intelligence as a design tool in many areas of renewable energy engineering.
genetic algorithms (GA) and fuzzy logic. The major objective of this paper is to illustrate how artificial
intelligence techniques might play an important role in modelling and prediction of the performance of
renewable energy systems in buildings. The paper outlines an understanding of how neural networks, genetic
algorithms and fuzzy systems operate by way of presenting a number of problems in the different disciplines of
renewable energy applications in buildings. The various applications are presented in a thematic rather than a
chronological or any other order. Results presented in this paper, are testimony to the potential of artificial
intelligence as a design tool in many areas of renewable energy engineering.
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