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 complexpolynomials 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. Presents a complete introduction to Hybrid Self-Organizing Modeling Systems INDICE: 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 SwarmOptimization and GMDH System.- GAME - Hybrid Self-Organizing Modeling System based on GMDH.
- ISBN: 978-3-642-01529-8
- Editorial: Springer
- Encuadernacion: Cartoné
- Páginas: 290
- Fecha Publicación: 01/06/2009
- Nº Volúmenes: 1
- Idioma: Inglés