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Studies in Computational Intelligence #211: Hybrid Self-Organizing Modeling Systems

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Studies in Computational Intelligence #211: Hybrid Self-Organizing Modeling Systems Cover

 

Synopses & Reviews

Publisher Comments:

The Group Method of Data Handling (GMDH) is a typical inductive modeling method that is built on principles of self-organization for modeling complex systems. However, it is known to often under-perform on non-parametric regression tasks, while time series modeling GMDH exhibits a tendency to find very complex polynomials that cannot model well future, unseen oscillations of the series. In order to alleviate these problems, GMDH has been recently hybridized with some computational intelligence (CI) techniques resulting in more robust and flexible hybrid intelligent systems for solving complex, real-world problems. The central theme of this book is to present in a very clear manner hybrids of some computational intelligence techniques and GMDH approach. The hybrids discussed in the book include GP-GMDH (Genetic Programming-GMDH) algorithm, GA-GMDH (Genetic Algorithm-GMDH) algorithm, DE-GMDH (Differential Evolution-GMDH) algorithm, and PSO-GMDH (Particle Swarm Optimization) algorithm. Also included is the description of the recently introduced GAME (Group Adaptive Models Evolution algorithm. The hybrid character of models and their self-organizing ability give these hybrid self-organizing modeling systems an advantage over standard data mining models. The modeling and data mining solutions of several real-life problems in the areas of engineering, bioinformatics, finance, and economics are presented in the chapters. The book will benefit amongst others, people who are working in the areas of neural networks, machine learning, artificial intelligence, complex system modeling and analysis, and optimization.

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 System.- Hybrid Particle Swarm Optimization and GMDH System.- GAME - Hybrid Self-Organizing Modeling System based on GMDH.

Product Details

ISBN:
9783642015298
Author:
Onwubolu, Godfrey C. (edt)
Publisher:
Springer
Editor:
Onwubolu, Godfrey C.
Author:
Onwubolu, Godfrey C.
Subject:
Applied
Subject:
Intelligence (AI) & Semantics
Subject:
Physics
Subject:
Computational intelligence
Subject:
GMDH
Subject:
Group Method of Data Handling
Subject:
Hybrid Computational Intelligence
Subject:
Hybrid Genetic Algorithms
Subject:
Hybrid Self-Organizing Modeling
Subject:
Appl.Mathematics/Computational Methods of Engineering
Subject:
Artificial Intelligence (incl. Robotics)
Subject:
Statistical Physics, Dynamical Systems and Complexity
Subject:
APPLICATIONS OF MATHEMATICS
Subject:
Mathematics-Applied
Copyright:
Edition Description:
Book
Series:
Studies in Computational Intelligence
Series Volume:
211
Publication Date:
20090611
Binding:
HARDCOVER
Language:
English
Pages:
304
Dimensions:
235 x 155 mm 1330 gr

Related Subjects

Computers and Internet » Artificial Intelligence » General
Computers and Internet » Computers Reference » General
Science and Mathematics » Mathematics » Applied
Science and Mathematics » Physics » General

Studies in Computational Intelligence #211: Hybrid Self-Organizing Modeling Systems New Hardcover
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