TY - JOUR
TI - Improved gray-encoded evolution algorithm based on chaos cluster for parameter optimization of moisture movement
AU - Yang Xiao-Hua
AU - Li Yu-Qi
AU - Wang Kai-Wen
AU - Sun Bo-Yang
AU - Ye Yi
AU - Li Mei-Shui
JN - Thermal Science
PY - 2017
VL - 21
IS - 4
SP - 1581
EP - 1585
PT - Article
AB - 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.