SOFT COMPUTING METHODS FOR PRACTICAL ENVIRONMENT SOLUTIONS

Nature provides inspiration and guidance in the creation of techniques, applications and new technologies in the fields of Artificial Intelligence and Soft Computing. Soft Computing Methods for Practical Environment Solutions: Techniques and Studies presents various practical applications of Soft Computing techniques in real-world situations and problems, aiming to show the enormous potential of such techniques in solving all kinds of problems, and thus, providing the latest advances in these techniques in an extensive state-of-the-art and a vast theoretical study. Ideal for students studying AI and researchers familiarizing themselves with such techniques, so to offer recent and novel applications, helping expand and explore new areas of research.

Marcos Gestal is an assistant professor in the Computer Science Faculty (University of A Coruña) and member of the research laboratory Artificial Neural Networks and Adaptative Systems. He has obtained his PhD degree in Computer Science in 2007, with a thesis about multimodal problem resolution using several approaches based on Genetic Algorithms. His actual research interests are focused on evolutionary computation (mainly genetic algorithms), artificial neural networks and their interaction to perform variable selection. Also he is interested in security task, so he is actually teaching in the information systems security subject. He has participated in several research projects and published papers in many international journals and books.

Daniel Rivero was born in A Coruña on the January, 30th 1978. He has obtained his MS degree in Computer Science by the University of A Coruña, A Coruña, Spain in 2001 and the PhD degree in Computer Science in 2007 by the same university. He is currently an assistant professor at the Faculty of Computer Science of the University of A Coruña. Before he gets that academic role, he has received different research grants from different administrations for more than four years. His main research interests are Artificial Neural Networks, Genetic Algorithms, Genetic Programming and Adaptative Systems.