Short-term localized weather forecasting by using different artificial neural network algorithm in tropical climate

Noor Zuraidin Mohd-Safar, David Lorater Ndzi, Ioannis Kagalidis, Yanyan Yang, Ammar Zakaria

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

2 Citations (Scopus)

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.

Original languageEnglish
Title of host publicationProceedings of SAI Intelligent Systems Conference (IntelliSys) 2016
EditorsYaxin Bi, Supriya Kapoor, Rahul Bhatia
PublisherSpringer International Publishing AG
Pages463-476
ISBN (Electronic)978-3-319-56991-8
ISBN (Print)978-3-319-56990-1
DOIs
Publication statusE-pub ahead of print - 23 Aug 2017
Externally publishedYes

Publication series

NameLecture Notes in Networks and Systems
PublisherSpringer
ISSN (Print)2367-3370

Keywords

  • artificial neural network, hort-term weather forecasting, tropical climate, ANN

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