Please use this identifier to cite or link to this item: http://ktisis.cut.ac.cy/handle/10488/878
Title: Artificial Intelligence in Renewable Energy Systems Modelling and Prediction
Authors: Kalogirou, Soteris A. 
Issue Date: 2002
Source: Proceedings of the World Renewable Energy Congress VII, Cologne, Germany
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.
Description: This paper is published in the World Renewable Energy Congress VII, Cologne, Germany.
URI: http://ktisis.cut.ac.cy/handle/10488/878
Appears in Collections:Δημοσιεύσεις σε συνέδρια/Conference papers

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