An adaptive RBF network optimised using a genetic algorithm applied to rainfall forecasting

C. Jareanpon, W. Pensuwon, R. Frank, N. Davey

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    10 Citations (Scopus)
    36 Downloads (Pure)

    Abstract

    Rainfall prediction is a challenging task especially in a modern world facing the major environmental problem of global warming. The proposed method uses an Adaptive Radial Basis Function neural network mode with a specially designed gerietic algoruhm (CA) to obtain the optimal model parameters. A significant feature of the Adaptive Radinl Basis Function network is that it is able creak new hidden units and solve the spread factor problem using a genetic algorithm. It is shown that the evolved parameter values improved performance.
    Original languageEnglish
    Title of host publicationIn: Procs IEEE Int Symp on Communications and Information Technologies (ISCIT 2004) Vol.2
    PublisherInstitute of Electrical and Electronics Engineers (IEEE)
    Pages1005-1010
    ISBN (Print)0-7803-8593-4
    DOIs
    Publication statusPublished - 2004

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