Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14279/2454
Title: Artificial Intelligence in Renewable Energy Applications in Buildings
Authors: Kalogirou, Soteris A. 
Major Field of Science: Engineering and Technology
Field Category: Environmental Engineering
Keywords: Artificial intelligence;Artificial neural networks;Performance;Renewable energy systems in buildings;Genetic algorithms
Issue Date: Jul-2005
Source: International Conference on the Integration of the Renewable Energy Systems into the Building Structures, 7-10 July, Patra, Greece
Conference: International Conference on The Integration of the Renewable Energy Systems into the Buildings Structures 
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.
URI: https://hdl.handle.net/20.500.14279/2454
Type: Conference Papers
Affiliation : Higher Technical Institute Cyprus 
Publication Type: Peer Reviewed
Appears in Collections:Δημοσιεύσεις σε συνέδρια /Conference papers or poster or presentation

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