Weather forecasting using merged long short-term memory model

Afan Galih Salman, Yaya Heryadi, Edi Abdurahman, Wayan Suparta

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

Over decades, weather forecasting has attracted researchers from worldwide communities due to itssignificant effect to global human life ranging from agriculture, air trafic control to public security. Although formal study on weather forecasting has been started since 19th century, research attention to weather forecasting tasks increased significantly after weather big data are widely available. This paper proposed merged-Long Short-term Memory for forecasting ground visibility at the airpot using timeseries of predictor variable combined with another variable as moderating variable. The proposed models were tested using weather timeseries data at Hang Nadim Airport, Batam. The experiment results showedthe best average accuracy for forecasting visibility using merged Long Short-term Memory model and temperature and dew point as a moderating variable was (88.6%); whilst, using basic Long Short-term Memory without moderating variablewasonly (83.8%) respectively (increased by 4.8%).

Original languageEnglish
Pages (from-to)377-385
Number of pages9
JournalBulletin of Electrical Engineering and Informatics
Volume7
Issue number3
DOIs
Publication statusPublished - 1 Sep 2018
Externally publishedYes

Fingerprint

Weather forecasting
weather forecasting
Memory Model
Weather
Forecasting
Visibility
visibility
weather
forecasting
Memory Term
dew point
Airports
Agriculture
agriculture
airports
Time Series Data
Predictors
Air
Long short-term memory
air

Keywords

  • Memory
  • Merged Long Short-term
  • Weather forecasting

ASJC Scopus subject areas

  • Computer Science (miscellaneous)
  • Control and Systems Engineering
  • Information Systems
  • Instrumentation
  • Hardware and Architecture
  • Computer Networks and Communications
  • Control and Optimization
  • Electrical and Electronic Engineering

Cite this

Weather forecasting using merged long short-term memory model. / Salman, Afan Galih; Heryadi, Yaya; Abdurahman, Edi; Suparta, Wayan.

In: Bulletin of Electrical Engineering and Informatics, Vol. 7, No. 3, 01.09.2018, p. 377-385.

Research output: Contribution to journalArticle

Salman, Afan Galih ; Heryadi, Yaya ; Abdurahman, Edi ; Suparta, Wayan. / Weather forecasting using merged long short-term memory model. In: Bulletin of Electrical Engineering and Informatics. 2018 ; Vol. 7, No. 3. pp. 377-385.
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