A Hybrid Optimization Method for Neural Tree Network Model

Neural tree network model has been successfully applied to solving large numbers of complex nonlinear problems in control area. The optimization of neural tree model contains: structure and parameter, the major problem in evolving structure without parameter information was noisy fitness evaluation...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Applied Mechanics and Materials Jg. 273; S. 820 - 825
Hauptverfasser: Qi, Feng, Ma, Ying Hong, Liu, Xi Yu
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Zurich Trans Tech Publications Ltd 2013
Schlagworte:
Neural Tree Network Model
Improved Hybrid Breeder Genetic Programming
Fitness Evaluation
Exponential Mutation
Time Series Forecasting
ISBN:9783037855881, 3037855886
ISSN:1660-9336, 1662-7482, 1662-7482
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:Neural tree network model has been successfully applied to solving large numbers of complex nonlinear problems in control area. The optimization of neural tree model contains: structure and parameter, the major problem in evolving structure without parameter information was noisy fitness evaluation problem, so an improved genetic programming algorithm is proposed to synthesize the optimization process. Simulation results on two time series prediction problems show that the proposed strategy is a potential method with better performance and effectiveness.
Bibliographie:Selected, peer reviewed papers from the 2nd International Conference on Innovation Manufacturing and Engineering Management (IMEM 2012), December 14-16, 2012, Chongqing, China
ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISBN:9783037855881
3037855886
ISSN:1660-9336
1662-7482
1662-7482
DOI:10.4028/www.scientific.net/AMM.273.820