Comparison of the efficacy of particle swarm optimization and stochastic gradient descent algorithms on multi-layer perceptron model to estimate longitudinal dispersion coefficients in natural streams

Comparison of the efficacy of particle swarm optimization and stochastic gradient descent algorithms on multi-layer perceptron model to estimate longitudinal dispersion coefficients in natural streams

Accurate estimation of the longitudinal dispersion coefficient (LDC) is essential for modeling the pollution status in rivers. This research investigates the capabilities of machine-learning methods such as multi-layer perceptron (MLP), multi-layer perceptron trained with particle swarm optimization...

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Bibliographic Details
Main Authors: Tao Hai, Hongwei Li, Shahab S. Band, Sadra Shadkani, Saeed Samadianfard, Sajjad Hashemi, Kwok-Wing Chau, Amir Mousavi
Format: Article
Language:English
Published: Taylor & Francis Group 2022-12-01
Series:Engineering Applications of Computational Fluid Mechanics
Subjects:
Longitudinal dispersion coefficient
multi-layer perceptron
particle swarm optimization
stochastic gradient descent
deep learning
statistical evaluation
Online Access:https://www.tandfonline.com/doi/10.1080/19942060.2022.2141896

Internet

https://www.tandfonline.com/doi/10.1080/19942060.2022.2141896

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