An assessment of Malaysian eArly warNing of convective system (MANCIS) to predict thunderstorm activities

Wayan Suparta, Wahyu Sasongko Putro, Mandeep Singh Jit Singh

Research output: Contribution to journalArticle

Abstract

Thunderstorm prediction is very important for Human activity particularly for the critical area. Since the initial of Malaysian eArly warNing of ConvectIve System (MANCIS) was constructed using ANFIS Human Expert model to predict thunderstorm activity, the capability of this model to predict thunderstorm activity are tested. A model in the MANCIS system was compared with establish software namely Weather Research and Forecasting (WRF) software to capture thunderstorm activity. The result showed MANCIS systems were outperformed the WRF EMS with the RMSE and average percent true of 0.491% and 0.572%, respectively.

Original languageEnglish
Pages (from-to)1428-1432
Number of pages5
JournalAdvanced Science Letters
Volume23
Issue number2
DOIs
Publication statusPublished - 1 Feb 2017

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Thunderstorms
Early Warning
convective system
Weather
thunderstorm
Software
Predict
Research
Human Activities
Forecasting
weather
software
Adaptive Neuro-fuzzy Inference System
human activity
Percent
Model
expert
prediction
Prediction
System of systems

Keywords

  • MANCIS
  • Statistical method
  • Tawau area
  • Weather research and forecasting (WRF)

ASJC Scopus subject areas

  • Computer Science(all)
  • Health(social science)
  • Mathematics(all)
  • Education
  • Environmental Science(all)
  • Engineering(all)
  • Energy(all)

Cite this

An assessment of Malaysian eArly warNing of convective system (MANCIS) to predict thunderstorm activities. / Suparta, Wayan; Putro, Wahyu Sasongko; Jit Singh, Mandeep Singh.

In: Advanced Science Letters, Vol. 23, No. 2, 01.02.2017, p. 1428-1432.

Research output: Contribution to journalArticle

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