PARTICLE SWARM OPTIMIZATION IN FEEDFORWARD NEURAL NETWORKS FOR RAINFALL-RUNOFF SIMULATION
Backpropagation neural networks have been effectively utilized by hydrologists in recent years to model various nonlinear hydrological processes due to their ability to generalize patterns in vague, noisy, ambiguous, and incomplete input and output datasets. However, the solutions may become stuck a...
Saved in:
Main Authors: | Kuok, King Kuok, Chiu, Po Chan, Md. Rezaur, Rahman, Chin, Mei Yun, Mohd Elfy, Mersal |
---|---|
Other Authors: | King Kuok, Kuok |
Format: | Book Chapter |
Language: | English |
Published: |
Cambridge Scholars Publishing
2024
|
Subjects: | |
Online Access: | http://ir.unimas.my/id/eprint/46907/1/Particle%20swarm.pdf http://ir.unimas.my/id/eprint/46907/ https://www.cambridgescholars.com/product/978-1-0364-0804-6 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Hourly rainfall-runoff modeling using particle swamp optimization feedforward neural network (PSONN)
by: Kuok, King Kuok, et al.
Published: (2009) -
Particle swarm optimization feedforward neural network for modeling runoff
by: Kuok, K. K., et al.
Published: (2010) -
Evaluation of daily rainfall-runoff model using multilayer perceptron and particle swarm optimization feed forward neural networks
by: Kuok, Kuok Kin, et al.
Published: (2010) -
Artificial neural networks (ANNS) for daily rainfall runoff modelling
by: Kuok, King Kuok, et al.
Published: (2011) -
Parameter optimization methods for calibrating tank model and neural network for rainfall-runoff modelling
by: Kuok, King Kuok
Published: (2010)