| 书目名称 | Hybrid Self-Organizing Modeling Systems |
| 编辑 | Godfrey C. Onwubolu |
| 视频video | |
| 概述 | Presents a complete introduction to Hybrid Self-Organizing Modeling Systems |
| 丛书名称 | Studies in Computational Intelligence |
| 图书封面 |  |
| 描述 | .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 |
| 出版日期 | Book 2009 |
| 关键词 | algorithm; algorithms; artificial intelligence; bioinformatics; complex system; complex systems; computati |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-3-642-01530-4 |
| isbn_softcover | 978-3-642-10182-3 |
| isbn_ebook | 978-3-642-01530-4Series ISSN 1860-949X Series E-ISSN 1860-9503 |
| issn_series | 1860-949X |
| copyright | Springer-Verlag Berlin Heidelberg 2009 |
发表于 2025-3-21 19:40:45
