Title: Demand estimation of water resources based on algorithm comparison

Authors: Junyan Wang; Jiangjiang Zhang; Xingjuan Cai; Yanyan Ma

Addresses: Jiangxi Province Key Laboratory of Water Information Cooperative Sensing and Intelligent Processing, Nanchang Institute of Technology, Nanchang 330099, China; Complex System and Computational Intelligence Laboratory, TaiYuan University of Science and Technology, Taiyuan 003024, China ' Complex System and Computational Intelligence Laboratory, TaiYuan University of Science and Technology, Taiyuan 003024, China ' Complex System and Computational Intelligence Laboratory, TaiYuan University of Science and Technology, Taiyuan 003024, China ' Shanxi Cloud Era TISCO Information Automation Technology Co., Ltd., Taiyuan, 030003, China

Abstract: Water is the source of life and the correct assessment of water resources is an important pre-requisite for the rational utilisation of water resources. In this paper, water resources are evaluated and predicted by three different algorithms, including Bat Algorithm (BA), Particle Swarm Optimisation (PSO) and Pigeon-Inspired Optimisation (PIO). Comparing the errors of water resources assessed for the three algorithms, we select an algorithm of the minimum error to predict the future water demand. In the experiments, firstly, the water data from 2003 to 2012 are used to find the optimal weights of the models. Then, the weight factor is combined with the given model to gain the error between predicted value and the remaining data (2013-2015). Finally, the simulation results show that PIO algorithm has a better performance compared with the BA and PSO algorithms.

Keywords: water resources; BA; bat algorithm; PSO; particle swarm optimisation; PIO; pigeon-inspired optimisation.

DOI: 10.1504/IJWMC.2019.099028

International Journal of Wireless and Mobile Computing, 2019 Vol.16 No.2, pp.110 - 116

Received: 05 Oct 2018
Accepted: 26 Oct 2018
Published online: 12 Apr 2019 *

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