Customer Reviews

Computational Intelligence in Time Series Forecasting: Theory and Engineering Applications (Advances in Industrial Control)

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The book is a summary of equations. These equations aren't explained whatsoever. Not even the symbols used in those equations are explained.

If you understand this book, you shouldn't have bought it, because you probably allready understood everything that was in it.

It looks nice, but it's not.

For the novice reader in this field of expertise this book is well suited. It does not mean that this book is not extensively explained, but the book is easy to understand since it is going step by step through many research result examples conducted in clear way. The author intended the book to be finished within approximately few weeks of intensively reading,and some prior knowledges. The presentation is awesome and includes up-to-date notions, namely Neural Network approach, Fuzzy Logic perspective and Evolutionary Computing as well. The Evolutionary Computing contains Genetic Algorithm, Genetic Programming, Evolutionary Strategy, Evolutionary Programming and Differential Evolution. The four last notions are left in concise for some reasons. Furthermore, the Hybrid method,i.e. Neuro-Fuzzy, is explained completely by many research results exploiting the robustness of Takagi-Sugeno fuzzy inference system applied with Mackey-Glass Chaotic time series and Wang data nonlinear inputs. The most recent developments are presented in some pages including Wavelet Networks, Fractal Based Network and Fuzzy Clustering.

However, this book is intended for postgraduate student, scientist and industrial workers in area of control, pattern recognition, robotic and many more.