Rain prediction using fuzzy rule based system in North-West Malaysia

Noor Zuraidin Mohd Safar, Azizul Azhar Ramli, Hirulnizam Mahdin, David Ndzi, Ku Muhammad Naim Ku Khalif

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)
161 Downloads (Pure)

Abstract

The warm and humid condition is the characteristic of Malaysia tropical climate. Prediction of rain occurrences is important for the daily operations and decisions for the country that rely on agriculture needs. However predicting rainfall is a complex problem because it is effected by the dynamic nature of the tropical weather parameters of atmospheric pressure, temperature, humidity, dew point and wind speed. Those parameters have been used in this study. The rainfall prediction are compared and analyzed. Fuzzy Logic and Fuzzy Inference System can deal with ambiguity that often occurred in meteorological prediction; it can easily incorporate with expert knowledge and empirical study into standard mathematical. This paper will determine the dependability of Fuzzy Logic approach in rainfall prediction within the given approximation of rainfall rate, exploring the use of Fuzzy Logic and to develop the fuzzified model for rainfall prediction. The accuracy of the proposed Fuzzy Inference System model yields 72%
Original languageEnglish
Pages (from-to)1572-1581
Number of pages10
JournalIndonesian Journal of Electrical Engineering and Computer Science
Volume14
Issue number3
Publication statusPublished - 3 Jun 2019

Keywords

  • Expert system
  • Fuzzy
  • Fuzzy inference system
  • Meteorology
  • Rain prediction
  • Rainfall forecast
  • Rainfall prediction
  • Soft computing
  • Tropical climate

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