期刊
WATER RESOURCES MANAGEMENT
卷 31, 期 6, 页码 1777-1794出版社
SPRINGER
DOI: 10.1007/s11269-017-1611-z
关键词
Longitudinal dispersion; PSO algorithm; Prediction; River; Accuracy
Accurate prediction of longitudinal dispersion coefficient (K) is a key element in studying of pollutant transport in rivers when the full cross sectional mixing has occurred. In this regard, several research studies have been carried out and different equations have been proposed. The predicted values of K obtained by different equations showed a great amount of uncertainty due to the complexity of the phenomenon. Therefore, there is still a need to make an improvement on the existing predictive models. In this study, a multi-objective particle swarm optimization (PSO) technique was used to derive new equations for predicting longitudinal dispersion coefficient in natural rivers. To do this, extensive field data, including hydraulic and geometrical characteristics of different rivers were applied. The results of this study were compared with those of the previous studies using the statistical error measures. The comparison revealed that the proposed model is superior to the previous ones. According to this study, PSO algorithm can be applied to improve the performance of the predictive equations by finding optimum values of the coefficients. The proposed model can be successfully applied to estimate the longitudinal dispersion coefficient for a wide range of rivers' characteristics.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据