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Lightning prediction using radiosonde data

This paper presents a concept of predicting lightning with the data from radiosonde using only a simple back propagation neural network model written in C code. The location of interest in this research is Kuala Lumpur International Airport (KLIA). In this model, the parameters related to wind were...

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Main Authors: Weng, L.Y., Omar, J.B., Siah, Y.K., Abidin, I.B.Z., Ahmad, S.K.
Format: Conference Paper
Language:English
Published: 2017
Online Access:http://dspace.uniten.edu.my/jspui/handle/123456789/6302
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spelling my.uniten.dspace-50392018-12-07T08:10:51Z Lightning prediction using radiosonde data Weng, L.Y. Omar, J.B. Siah, Y.K. Abidin, I.B.Z. Ahmad, S.K. This paper presents a concept of predicting lightning with the data from radiosonde using only a simple back propagation neural network model written in C code. The location of interest in this research is Kuala Lumpur International Airport (KLIA). In this model, the parameters related to wind were disregarded. Preliminary results indicate that this method shows some positive results. Future work should include wind parameters to fully capture all properties for lightning formation, subsequently its prediction. 2017-11-14T03:21:34Z 2017-11-14T03:21:34Z 2008 Conference Paper http://dspace.uniten.edu.my/jspui/handle/123456789/6302 10.1109/ICICCI.2010.83 en Proceedings - 2010 International Conference on Intelligent Computing and Cognitive Informatics, ICICCI 2010 2010, Article number 5566013, Pages 152-155
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
language English
description This paper presents a concept of predicting lightning with the data from radiosonde using only a simple back propagation neural network model written in C code. The location of interest in this research is Kuala Lumpur International Airport (KLIA). In this model, the parameters related to wind were disregarded. Preliminary results indicate that this method shows some positive results. Future work should include wind parameters to fully capture all properties for lightning formation, subsequently its prediction.
format Conference Paper
author Weng, L.Y.
Omar, J.B.
Siah, Y.K.
Abidin, I.B.Z.
Ahmad, S.K.
spellingShingle Weng, L.Y.
Omar, J.B.
Siah, Y.K.
Abidin, I.B.Z.
Ahmad, S.K.
Lightning prediction using radiosonde data
author_facet Weng, L.Y.
Omar, J.B.
Siah, Y.K.
Abidin, I.B.Z.
Ahmad, S.K.
author_sort Weng, L.Y.
title Lightning prediction using radiosonde data
title_short Lightning prediction using radiosonde data
title_full Lightning prediction using radiosonde data
title_fullStr Lightning prediction using radiosonde data
title_full_unstemmed Lightning prediction using radiosonde data
title_sort lightning prediction using radiosonde data
publishDate 2017
url http://dspace.uniten.edu.my/jspui/handle/123456789/6302
_version_ 1644493597566828544
score 13.223943

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