Overview

Models form the basis of any decision. They are used in di?erent context and for di?erent purposes: for identi?cation, prediction, classi?cation, or control of complex systems. Modeling is done theory-driven by logical-mathematical methods or data-driven based on observational data of the system and some algorithm or software for analyzing this data. Today, this approach is s- marized as Data Mining. There are many Data Mining algorithms known like Arti?cial Neural N- works, Bayesian Networks, Decision Trees, Support Vector Machines. This book focuses on another method: the Group Method of Data Handling. - thoughthismethodologyhasnotyetbeenwellrecognizedintheinternational science community asa verypowerfulmathematicalmodeling andknowledge extraction technology, it has a long history. Developed in 1968bythe Ukrainianscientist A.G. Ivakhnenko it combines the black-box approach and the connectionism of Arti?cial Neural Networks with well-proven Statistical Learning methods and with more behavior- justi?ed elements of inductive self-organization.Over the past 40 years it has been improving and evolving, ?rst by works in the ?eld of what was known in the U.S.A. as Adaptive Learning Networks in the 1970s and 1980s and later by signi? cantcontributions from scientists from Japan,China, Ukraine, Germany. Many papers and books have been published on this modeling technology, the vast majority of them in Ukrainian and Russian language.

Full Product Details

Author:   Godfrey C. Onwubolu
Publisher:   Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
Imprint:   Springer-Verlag Berlin and Heidelberg GmbH & Co. K
Edition:   Softcover reprint of hardcover 1st ed. 2009
Volume:   211
Dimensions:   Width: 15.50cm , Height: 1.60cm , Length: 23.50cm
Weight:   0.468kg
ISBN:  

9783642101823

ISBN 10:   3642101828
Pages:   282
Publication Date:   28 October 2010
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   In Print  
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Table of Contents

Hybrid Computational Intelligence and GMDH Systems.- Hybrid Genetic Programming and GMDH System: STROGANOFF.- Hybrid Genetic Algorithm and GMDH System.- Hybrid Differential Evolution and GMDH Systems.- Hybrid Particle Swarm Optimization and GMDH System.- GAME – Hybrid Self-Organizing Modeling System Based on GMDH.

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