MATEC Web Conf.
Volume 246, 20182018 International Symposium on Water System Operations (ISWSO 2018)
|Number of page(s)||9|
|Section||Main Session: Water System Operations|
|Published online||07 December 2018|
Water demand forecast model of Least Squares Support Vector Machine based on Particle Swarm Optimization
1 Zhejiang Institute of Hydraulics & Estuary, No.50, Fengqi East Road, Hangzhou 310020, China.
2 College of Hydrology and Water Resources, Hohai University, No.1, Xikang Road, Nanjing 210098, China.
a Corresponding author: email@example.com
In order to solve the problem of precision of water demand forecast model, a coupled water demand forecast model of particle swarm optimization (PSO) algorithm and least squares support vector machine (LS-SVM) are proposed in this paper. A PSO-LSSVM model based on parameter optimization was constructed in a coastal area of Binhai, Jiangsu Province, and the total water demand in 2009 and 2010 were simulated and forecasted with the absolute value of the relative errors less than 2.1%. The results showed that the model had good simulation effect and strong generalization performance, and can be widely used to solve the problem of small- sample, nonlinear and high dimensional water demand forecast.
© The Authors, published by EDP Sciences, 2018
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