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Ensemble prediction of monthly mean rainfall with a Particle Swarm Optimization-neural network model | IEEE Conference Publication | IEEE Xplore

Ensemble prediction of monthly mean rainfall with a Particle Swarm Optimization-neural network model


Abstract:

A nonlinear statistical ensemble prediction modeling method has been developed for predicting monthly mean rainfall using Particle Swarm Optimization (PSO) algorithm and ...Show More

Abstract:

A nonlinear statistical ensemble prediction modeling method has been developed for predicting monthly mean rainfall using Particle Swarm Optimization (PSO) algorithm and neural network (NN) technique. Comparison results of prediction experiments show that the PSO-NN ensemble prediction (PNNEP) model is superior to the traditional linear statistical forecast method in prediction capability. Computation and analysis of the PNNEP also demonstrate that the prediction of the ensemble model integrates predictions of dozens of ensemble members and the network structure of each member is objectively determined by means of PSO algorithm, so the generalization capacity of the ensemble prediction model is also enhanced, suggesting that the PNNEP model opens up a vast range of possibilities for operational weather prediction.
Date of Conference: 08-10 August 2012
Date Added to IEEE Xplore: 17 September 2012
ISBN Information:
Conference Location: Las Vegas, NV, USA

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