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Synopsis
Artificial Neural Networks in Real-Life Applications offers an outlook on the most recent works in the field of artificial neural networks (ANN). It includes theoretical developments of the ANN area and applications of these systems, using intelligent characteristics for adaptability, automatic learning, classification, prediction and even artistic creation. Artificial Neural Networks in Real-Life Applications is a summary of recent advances in the ANN area from a practical perspective. It shows studies of the applications in time series forecasting, extraction of knowledge, civil engineering, economical field, artistic creation (music), cost minimization, intruder detection, and many others, making it a very important source of ideas for research in this area.
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About the Author
Juan R. Rabunal is assistant professor in the Department of Information and Communications Technologies of the University of A Coruna. He finished his studies on Computer Engineering in 1996, and on 2002 he became Doctor in Computer Science with his thesis ""Methodology for the Development of Knowledge Extraction Systems in ANNs"". He has worked on several Spanish and European projects, and he has published many books and papers on several international journals. He is currently working on Evolutionary Computation, Artificial Neural Networks and Knowledge Extraction systems. Julian Dorado is associate professor in the Faculty of Computer Science in the University of a Coruna. He finished his graduate in Computer Science in 1994. In 1999, he became Ph.D, with a special mention of European Doctor. In 2004, he has finished his graduate in Biology. He has worked as a teacher of the University for more than 8 years. He has published many books and papers on several journals and international congresses. He is at present working on Bioinformatics, Evolutionary Computing, Artificial Neural Networks, Computer Graphics and Data Mining.
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Artificial Neural Networks in Real-Life Applications.
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