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A Novel Nonparametric Regression Ensemble for Rainfall Forecasting Using Particle Swarm Optimization Technique Coupled with Artificial Neural Network

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Advances in Neural Networks – ISNN 2009 (ISNN 2009)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5553))

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Abstract

In this study, we propose a novel nonparametric regression (NR) ensemble rainfall forecasting model integrating generalized particle swarm optimization (PSO) with artificial neural network (ANN). First of all, the PSO algorithm is used to evolve neural network architecture and connection weights. The evolved neural network architecture and connection weights are input into a new neural network.The new neural network is trained using back-propagation (BP) algorithm, generating different individual neural network. Then, the principal component analysis (PCA) technology is adopted to extract ensemble members. Finally, the NR is used for nonlinear ensemble model. Empirical results obtained reveal that the prediction by using the NR ensemble model is generally better than those obtained using other models presented in this study in terms of the same evaluation measurements. For illustration and testing reveal that the NR ensemble model proposed can be used as an alternative forecasting tool for a Meteorological application in achieving greater forecasting accuracy and improving prediction quality further.

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Author information

Authors and Affiliations

  1. Department of Mathematics and Computer, Liuzhou Teacher College, Guangxi, Liuzhou, China

    Jiansheng Wu

  2. Department of Computer, University of Science and Technology of China, Hefei, Anhui, China

    Enhong Chen

Authors
  1. Jiansheng Wu
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  2. Enhong Chen
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Editor information

Editors and Affiliations

  1. Departamento de Control Automático, CINVESTAV-IPN, A.P. 14-740, Av.IPN 2508, 07360, México D.F., México

    Wen Yu

  2. Deptartment of Electrical and Computer Engineering, Stevens Institute of Technology, Hoboken, USA

    Haibo He

  3. Dept. of Electrical and Computer Engineering, South Dakota School of Mines & Technology, 501 E. St. Joseph Street, SD 57701, Rapid City, USA

    Nian Zhang

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Wu, J., Chen, E. (2009). A Novel Nonparametric Regression Ensemble for Rainfall Forecasting Using Particle Swarm Optimization Technique Coupled with Artificial Neural Network. In: Yu, W., He, H., Zhang, N. (eds) Advances in Neural Networks – ISNN 2009. ISNN 2009. Lecture Notes in Computer Science, vol 5553. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01513-7_6

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  • DOI: https://doi.org/10.1007/978-3-642-01513-7_6

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-01512-0

  • Online ISBN: 978-3-642-01513-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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