A fractional-order genetic algorithm for parameter optimization of the moisture movement in a bio-retention system

Abstract

A bio-retention system is an important measure for non-point source pollution control. In order to improve the calculation precision for parameter optimization of the moisture movement in a bio-retention system, a real-encoded genetic algo-rithm based on the fractional-order operation is proposed, in which initial popu-lations are generated by random mapping, and the searching range is automati-cally renewed with the excellent individuals by fractional-order particle swarm optimization operation. Its efficiency is verified experimentally. The results indi-cate that the absolute error by the fractional-order operation decreases by 67.73%, 62.23%, and 4.16%, and the relative error decreases by 42.88%, 35.76%, and 6.77%, respectively, compared to those by the standard binary-encoded genetic algorithm, random algorithm, and the particle swarm optimiza-tion algorithm. The fractional-order operation has higher precision and it is good for the practical parameter optimization in ecological environment systems.