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Short-Term Localized Weather Forecasting by Using Different Artificial Neural Network Algorithm in Tropical Climate

  • Noor Zuraidin Mohd-SafarEmail author
  • David Ndzi
  • Ioannis Kagalidis
  • Yanyang Yang
  • Ammar Zakaria
Conference paper
Part of the Lecture Notes in Networks and Systems book series (LNNS, volume 16)

Abstract

This paper evaluates the performance of localized weather forecasting model using Artificial Neural Network (ANN) with different ANN algorithms in a tropical climate. Three ANN algorithms namely, Levenberg-Marquardt, Bayesian Regularization and Scaled Conjugate Gradient are used in the short-term weather forecasting model. The study focuses on the data from North-West Malaysia (Chuping). Meteorological data such as atmospheric pressure, temperature, dew point, humidity and wind speed are used as input parameters. One hour ahead forecasted results for atmospheric pressure, temperature and humidity were compared and analyzed and they show that ANN with Levenberg-Marquardt algorithm performs best.

Keywords

Artificial neural network ANN Short-term weather forecasting Neural network Soft computing Tropics Tropical climate 

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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • Noor Zuraidin Mohd-Safar
    • 1
    Email author
  • David Ndzi
    • 1
  • Ioannis Kagalidis
    • 1
  • Yanyang Yang
    • 1
  • Ammar Zakaria
    • 2
  1. 1.School of EngineeringUniversity of PortsmouthPortsmouthUK
  2. 2.School of Mechatronic EngineeringUniversiti Malaysia PerlisArauMalaysia

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