THERMAL SCIENCE

International Scientific Journal

IMPROVED GRAY-ENCODED EVOLUTION ALGORITHM BASED ON CHAOS CLUSTER FOR PARAMETER OPTIMIZATION OF MOISTURE MOVEMENT

ABSTRACT
To improve computational precision for parameter optimization of the van Genuchten model in simulating moisture movement in environment protection, an improved gray-encoded evolution algorithm based on chaos cluster (IGEACC) is proposed, in which an initial population is generated by chaotic mapping, and the searching range is automatically renewed with the excellent individuals by chaos cluster operation. Its efficiency is verified experimentally. The results indicate that the absolute error by the IGEACC decreases by 7.52% and 40.40%, respectively, and the relative error decreases by 12.65% and 49.95%, respectively, compared to those by the standard binary-encoded evolution algorithm (SBEA), and the particle swarm optimization algorithm (PSOA). IGEACC has higher precision and it is good for the global optimization in the practical parameter optimization in environment system.
KEYWORDS
PAPER SUBMITTED: 2016-05-29
PAPER REVISED: 2016-09-01
PAPER ACCEPTED: 2016-10-25
PUBLISHED ONLINE: 2017-09-09
DOI REFERENCE: https://doi.org/10.2298/TSCI160529038Y
CITATION EXPORT: view in browser or download as text file
THERMAL SCIENCE YEAR 2017, VOLUME 21, ISSUE 4, PAGES [1581 - 1585]
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© 2017 Society of Thermal Engineers of Serbia. Published by the Vinča Institute of Nuclear Sciences, Belgrade, Serbia. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International licence