Predicting longitudinal dispersion coefficient using ensemble models and optimized multi-layer perceptron models
Prediction of the longitudinal dispersion coefficient (LDC) is essential for the river and water resources engineering and environmental management. This study proposes ensemble models for predicting LDC based on multilayer perceptron (MULP) methods and optimization algorithms. The honey badger opti...
Saved in:
Main Authors: | Gholami M., Ghanbari-Adivi E., Ehteram M., Singh V.P., Najah Ahmed A., Mosavi A., El-Shafie A. |
---|---|
Other Authors: | 56973673400 |
Format: | Article |
Published: |
Ain Shams University
2024
|
Subjects: | |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
A hybrid particle swarm optimization approach and its application to solving portfolio selection problems
by: Shamshul Bahar, Yaakob, Prof. Madya, et al.
Published: (2011) -
Fitness-guided particle swarm optimization with adaptive Newton-Raphson for photovoltaic model parameter estimation
by: Premkumar M., et al.
Published: (2025) -
Flood mapping based on novel ensemble modeling involving the deep learning, Harris Hawk optimization algorithm and stacking based machine learning
by: Costache R., et al.
Published: (2025) -
Investigating the Performance of Deep Reinforcement Learning-Based MPPT Algorithm under Partial Shading Condition
by: Yew W.H., et al.
Published: (2024) -
Particle Swarm Optimization (PSO) and its application in power converter system
by: Naziha, Ahmad Azli, Dr., et al.
Published: (2012)