Research on Rainfall Prediction Based on VMD-PSO-LSSVM
Rainfall events are highly random.In order to scientifically and effectively predict complex rainfall,a rainfall pre-diction model based on VMD-PSO-LSSVM is proposed.Firstly,VMD method is used to decompose the original rainfall series.Then,particle swarm optimization is used to optimize the key parameters of least squares support vector machine,and a series of subsequences are predicted by accurately constructed prediction model.Finally,all prediction subsequences are synthesized to ob-tain the final prediction results.The simulation results show that the prediction results of VMD-PSO-LSSVM model have less error and higher accuracy.It can become an effective rainfall prediction tool,provide reference for agriculture and water conservancy de-partments to make water resources management decisions,and reduce the risk of drought and flood disasters.
variational modal decompositionparticle swarm optimizationleast squares support vector machinerainfall
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