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Artificial Intelligence Techniques for Modern Energy Applications

Artificial Intelligence Techniques for Modern Energy Applications

Soteris Kalogirou, Kostas Metaxiotis, Adel Mellit
Copyright: © 2010 |Pages: 39
ISBN13: 9781605667379|ISBN10: 1605667374|ISBN13 Softcover: 9781616924225|EISBN13: 9781605667386
DOI: 10.4018/978-1-60566-737-9.ch001
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MLA

Kalogirou, Soteris, et al. "Artificial Intelligence Techniques for Modern Energy Applications." Intelligent Information Systems and Knowledge Management for Energy: Applications for Decision Support, Usage, and Environmental Protection, edited by Kostas Metaxiotis, IGI Global, 2010, pp. 1-39. https://doi.org/10.4018/978-1-60566-737-9.ch001

APA

Kalogirou, S., Metaxiotis, K., & Mellit, A. (2010). Artificial Intelligence Techniques for Modern Energy Applications. In K. Metaxiotis (Ed.), Intelligent Information Systems and Knowledge Management for Energy: Applications for Decision Support, Usage, and Environmental Protection (pp. 1-39). IGI Global. https://doi.org/10.4018/978-1-60566-737-9.ch001

Chicago

Kalogirou, Soteris, Kostas Metaxiotis, and Adel Mellit. "Artificial Intelligence Techniques for Modern Energy Applications." In Intelligent Information Systems and Knowledge Management for Energy: Applications for Decision Support, Usage, and Environmental Protection, edited by Kostas Metaxiotis, 1-39. Hershey, PA: IGI Global, 2010. https://doi.org/10.4018/978-1-60566-737-9.ch001

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Abstract

Artificial intelligence (AI) techniques are becoming useful as alternate approaches to conventional techniques or as components of integrated systems. They have been used to solve complicated practical problems in various areas and nowadays are very popular. They are widely accepted as a technology offering an alternative way to tackle complex and ill-defined problems. They can learn from examples, are fault tolerant in the sense that they are able to handle noisy and incomplete data, are able to deal with non-linear problems and once trained can perform prediction and generalization at very high speed. AI-based systems are being developed and deployed worldwide in a wide variety of applications, mainly because of their symbolic reasoning, flexibility and explanation capabilities. They have been used in diverse applications in control, robotics, pattern recognition, forecasting, medicine, power systems, manufacturing, optimization, signal processing and social/psychological sciences. They are particularly useful in system modeling such as in implementing complex mappings and system identification. This chapter presents a review of the main AI techniques such as expert systems, artificial neural networks, genetic algorithms, fuzzy logic and hybrid systems, which combine two or more techniques. It also outlines some applications in the energy sector.

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