Rainfall prediction in Semi-arid regions in Jordan using back propagation neural networks

Bilal Zahran, Abdelwadood Mesleh, Mohammed Matouq, Omar Alheyasat, Tariq Alwada'n

    Research output: Contribution to journalArticlepeer-review

    Abstract

    In Jordan, agriculture and irrigation depend highly on rainfalls. Rainfall prediction
    is a challenging area of investigation for scientists. In this paper, a precipitation prediction model
    using artificial neural networks (ANNs) is proposed. The seasonal amount of rainfall in several
    areas in Jordan is predicted using rainfall rate time-series data, these rainfall rate data has been
    recorded from 26 stations located in different areas in Jordan. A feed forward ANN based on
    backpropagation (BP) is designed and trained to predict the future rainfalls in Jordan. Results are
    encouraging and accurate for rainfall prediction in Jordan
    Original languageEnglish
    Pages (from-to)158-162
    Number of pages5
    JournalInternational Journal on Engineering Applications
    Volume3
    Issue number6
    Publication statusPublished - 30 Nov 2015

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