Streamflow prediction with large climate indices using several hybrid multilayer perceptrons and copula Bayesian model averaging

Streamflow prediction with large climate indices using several hybrid multilayer perceptrons and copula Bayesian model averaging

Streamflow prediction help the modelers to manage water resources in watersheds. It gives essential information for flood control and reservoir operation. This study uses the copula-based -Bayesian model averaging (CBMA) as an improved version of the BMA model for predicting streamflow in the Golok...

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Bibliographic Details
Main Authors: Ahmed, A.N (Author), Ehteram, M. (Author), El-Shafie, A. (Author), Huang, Y.F (Author), Mosavi, A. (Author), Panahi, F. (Author)
Format: Article
Language:English
Published: Elsevier B.V. 2021
Subjects:
Artificial intelligence
artificial neural network
Bat algorithms
Bayesian model averaging
Bayesian modelling
Bayesian networks
Climate models
Copula bayesian model
Copula Bayesian model
flood
flood control
Flood control
Floods
Forecasting
Gamma test
inclusive multiple model
Inclusive multiple model
Information management
Inverse problems
Kelantan
Malaysia
Mean square error
Multilayer neural networks
multilayer perceptron
Multilayers
Multilayers perceptrons
Multiple-modeling
Natural hazard
natural hazards
Normal distribution
North Atlantic Oscillation
Optimization algorithms
Particle swarm optimization (PSO)
perception
reservoir
Reservoir management
Reservoirs (water)
Risk management
Rivers
Stream flow
streamflow
uncertainty analysis
Uncertainty analysis
West Malaysia
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