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An Adaptive Invasive Weed Optimization Algorithm.

Authors :
Peng, Shuo
Ouyang, A.-J.
Zhang, Jeff Jun
Source :
International Journal of Pattern Recognition & Artificial Intelligence. Mar2015, Vol. 29 Issue 2, p-1. 19p.
Publication Year :
2015

Abstract

With regards to the low search accuracy of the basic invasive weed optimization algorithm which is easy to get into local extremum, this paper proposes an adaptive invasive weed optimization (AIWO) algorithm. The algorithm sets the initial step size and the final step size as the adaptive step size to guide the global search of the algorithm, and it is applied to 20 famous benchmark functions for a test, the results of which show that the AIWO algorithm owns better global optimization search capacity, faster convergence speed and higher computation accuracy compared with other advanced algorithms. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
02180014
Volume :
29
Issue :
2
Database :
Academic Search Index
Journal :
International Journal of Pattern Recognition & Artificial Intelligence
Publication Type :
Academic Journal
Accession number :
108351160
Full Text :
https://doi.org/10.1142/S0218001415590041