Gene Expression Programming Based on Parallel Tabu Search for Improving Model Accuracy

Xue Dong Zhang; Jing Li

doi:10.4028/www.scientific.net/AMM.411-414.1930

Paper Titles

Study on Free Search for Combinatorial Optimization Problem
p.1904

Study on Transformation Mechanism of Driver's Propensity under Two-Lane Conditions
p.1911

Attribute Reduction Algorithm on Balancing Profit and Risk
p.1919

A Syntactic Reordering Model of Chinese Special Sentences for Patent Machine Translation
p.1923

Gene Expression Programming Based on Parallel Tabu Search for Improving Model Accuracy
p.1930

A Study on Approximation Performances of Improved Bp Neural Networks Based on LM Algorithms
p.1935

An Ant Colony Optimization Algorithm for Selection Problem
p.1939

A New Coordination Model for Ill-Posed Bilevel Programming Problem
p.1943

Study for Evaluation Method Based on Neural Networks
p.1948

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 411-414Gene Expression Programming Based on Parallel Tabu...

Gene Expression Programming Based on Parallel Tabu Search for Improving Model Accuracy

Abstract:

To improve model accuracy,tabu search is introduced to Gene Expression Programming (GEP) and impoves GEPs local search ability, Gene Expression Programming Based on Parallel Tabu Search (PTS-GEP) is proposed. In PTS-GEP, the research conducts experiment over the data from previously reported research and compares the result to two other algorithms namely simple GEP, UC-GEP. The results demonstrate the optimal performance of PTS-GEP in model accuracy.

You might also be interested in these eBooks

View Preview

Info:

Periodical:

Applied Mechanics and Materials (Volumes 411-414)

Pages:

1930-1934

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.411-414.1930

Citation:

Cite this paper

Online since:

September 2013

Authors:

Xue Dong Zhang, Jing Li

Keywords:

Gene Expression Programming, Model Accuracy, Tabu Search

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

References

[1] Ferreira C. Gene Expression Programming: A New Adaptive Algorithm for Solving Problems[J]. Complex Systems, 2001, Vol. 13, issue 2: 87-129.

Google Scholar

[2] Ferreira C. Function finding and the creation of numerical constants in gene expression programming[EB/OL]. 2002, http: /www. gene-expression-programming. com/webpapers/Ferreira-WSC7. pdf.

DOI: 10.1007/978-1-4471-3744-3_25

Google Scholar

[3] HU Jian-jun, TANG Chang-jie, PENG Jing, et al. VPS-GEP: Skipping from Local Optimization Fast Algorithm [J]. Journal of Sichuan University(Engineering Science Edition), Vol. 30(1) 2007: 128-133.

Google Scholar

[4] Xu Kaikuo, Liu Yintian, Tang Rong, et al. A Novel Method for Real Parameter Optimization Based on Gene Expression Programming[J]. Applied Soft Computing Journal, DOI=10. 1016/j. asoc. 2008. 09. 007.

Google Scholar

[5] Yuan Changan, Tang Changjie, et al. Intelligent function model discovery system based upon gene expression programming[J]. Journal of Computational Information Systems, 2006, 2(4): 1299-1307.

Google Scholar

[6] DENG Song, WANG Ru-chuan. Gene expression programming function mining based upon grid [J]. Journal on Communications, 2008, Vol. 29(6) : 69-74.

Google Scholar

[7] DENG Song WANG Ru-chuan REN Xun-yi. Distributed Function Mining for GEP on Grid Services [J]. Computer Science, 2009，Vol. 36 (11) : 177-181.

Google Scholar

[8] QIAN Xiao-shan, YANG Chun-hua. Improved gene expression programming algorithm tested by predicting stock indexes [J]. , CAAI Transactions on Intelligent Systems, 2010，Vol. 5(5) : 303-307.

Google Scholar