Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14279/2484
Title: Artificial Intelligence in Renewable Energy Systems Modelling and Prediction
Authors: Kalogirou, Soteris A. 
Major Field of Science: Engineering and Technology
Field Category: Environmental Engineering
Keywords: Artificial intelligence;Artificial neural networks;Renewable energy systems
Issue Date: 2002
Source: World Renewable Energy Congress VII, 2002, 29 June – 5 July, Cologne, Germany
Conference: World Renewable Energy Congress VII 
Abstract: The possibility of developing a machine that would “think” has intrigued human beings since ancient times. Artificial intelligence (AI) systems comprise two major areas, expert systems (ES) and artificial neural networks (ANNs). 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. The paper outlines an understanding of how expert systems and neural networks operate by way of presenting a number of problems in the different disciplines of renewable energy engineering. The various applications of expert systems and neural networks 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/20.500.14279/2484
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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