Open AccessImproved gray-encoded evolution algorithm based on chaos cluster for parameter optimization of moisture movement
Author(s) -
Xiaohua Yang,
Yuqi Li,
Kaiwen Wang,
Sun Bo-yang,
Yi Ye,
Meishui Li
Publication year - 2017
Publication title -
thermal science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.339
H-Index - 43
eISSN - 2334-7163
pISSN - 0354-9836
DOI - 10.2298/tsci160529038y
Subject(s) - chaotic , chaos (operating system) , algorithm , particle swarm optimization , computer science , cluster (spacecraft) , population , optimization algorithm , global optimization , range (aeronautics) , mathematical optimization , mathematics , artificial intelligence , computer security , demography , composite material , sociology , programming language , materials science
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 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 improved gray-encoded evolution algorithm based on chaos cluster 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, and the particle swarm optimization algorithm. Improved gray-encoded evolution algorithm based on chaos cluster has higher precision and it is good for the global optimization in the practical parameter optimization in environment system
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