Title: A new differential evolution based on Gaussian sampling for forecasting urban water resources demand

Authors: Wenjun Wang; Hui Wang

Addresses: School of Business Administration, Nanchang Institute of Technology, Nanchang 330099, China ' Jiangxi Province Key Laboratory of Water Information Cooperative Sensing and Intelligent Processing, Nanchang Institute of Technology, Nanchang 330099, China

Abstract: In order to improve the performance of differential evolution (DE), this paper presents a new DE variant based on Gaussian sampling (NDEGS) to forecast urban water resources demand. In NDEGS, two strategies are employed. First, Gaussian sampling is used to replace the mutation operation. Second, a dynamic population method is employed to adjust the population size during the search process. In the simulation experiment, the water resources demand in Nanchang city of China is considered as a case study. Simulation results demonstrate that NDEGS can achieve promising prediction accuracy.

Keywords: differential evolution; Gaussian sampling; dynamic population size; water resources demand; forecasting; optimisation.

DOI: 10.1504/IJCSM.2018.091750

International Journal of Computing Science and Mathematics, 2018 Vol.9 No.2, pp.155 - 162

Received: 30 Nov 2017
Accepted: 02 Jan 2018

Published online: 30 Apr 2018 *

Full-text access for editors Access for subscribers Purchase this article Comment on this article