Reliability-based design and implementation of crow search algorithm for longitudinal dispersion coefficient estimation in rivers
Open Access
- 8 March 2021
- journal article
- research article
- Published by Springer Science and Business Media LLC in Environmental Science and Pollution Research
- Vol. 28 (27), 35971-35990
- https://doi.org/10.1007/s11356-021-12651-0
Abstract
The longitudinal dispersion coefficient (LDC) of river pollutants is considered as one of the prominent water quality parameters. In this regard, numerous research studies have been conducted in recent years, and various equations have been extracted based on hydrodynamic and geometric elements. LDC’s estimated values obtained using different equations reveal a significant uncertainty due to this phenomenon’s complexity. In the present study, the crow search algorithm (CSA) is applied to increase the equation’s precision by employing evolutionary polynomial regression (EPR) to model an extensive amount of geometrical and hydraulic data. The results indicate that the CSA improves the performance of EPR in terms of R2 (0.8), Willmott’s index of agreement (0.93), Nash–Sutcliffe efficiency (0.77), and overall index (0.84). In addition, the reliability analysis of the proposed equation (i.e., CSA) reduced the failure probability (Pf) when the value of the failure state containing 50 to 600 m2/s is increasing for the Pf determination using the Monte Carlo simulation. The best-fitted function for correct failure probability prediction was the power with R2 = 0.98 compared with linear and exponential functions.Funding Information
- European Commission (EFOP-3.6.1-16-2016-00010)
- Alexander von Humboldt-Stiftung
This publication has 84 references indexed in Scilit:
- Modeling dimensionless longitudinal dispersion coefficient in natural streams using artificial intelligence methodsKSCE Journal of Civil Engineering, 2013
- Predicting Longitudinal Dispersion Coefficients in Sinuous Rivers by Genetic AlgorithmJournal of Hydrology and Hydromechanics, 2013
- Regression Kriging Analysis for Longitudinal Dispersion CoefficientWater Resources Management, 2013
- Prediction of longitudinal dispersion coefficients in natural rivers using genetic algorithmHydrology Research, 2009
- Predicting the Longitudinal Dispersion Coefficient Using Support Vector Machine and Adaptive Neuro-Fuzzy Inference System TechniquesEnvironmental Engineering Science, 2009
- Advances in data-driven analyses and modelling using EPR-MOGAJournal of Hydroinformatics, 2009
- An expert system for predicting longitudinal dispersion coefficient in natural streams by using ANFISExpert Systems with Applications, 2009
- GA-optimized model predicts dispersion coefficient in natural channelsHydrology Research, 2009
- Predicting longitudinal dispersion coefficient in natural streams by artificial intelligence methodsHydrological Processes, 2008
- Longitudinal Dispersion Coefficient Modeling in Natural Channels using Fuzzy LogicCLEAN - Soil, Air, Water, 2007