Data Mining: Theory and Practice

We have the data; how do we get the knowledge? This book demonstrates how traditional data mining concepts and techniques can be enhanced by advances in computational intelligence, such as fuzzy type-2 arithmetic queries and trending, growing neural gas, 3D self-organizing maps, CAVE visual data mining, fuzzy-neural clustering algorithms, and combinations of these. The techniques are demonstrated with examples of industry hot topics such as smart grids, hybrid energy production, and the modeling of nuclear plant components. This book offers a theoretical framework for major issues in data mining, followed by several case studies of industrial applications.