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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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Bibliographic Details
Main Authors: Weng L.Y., Omar J.B., Siah Y.K., Abidin I.B.Z., Ahmad S.K.
Other Authors: 26326032700
Format: Conference paper
Published: 2023
Subjects:
Artificial intelligence
Lightning forecasting
Lightning prediction
Neural networks
Electric load forecasting
Lightning
Radiosondes
Back propagation neural networks
C codes
Kuala lumpur international airports
Radiosonde datum
Wind parameters
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id my.uniten.dspace-29717
record_format dspace
spelling my.uniten.dspace-297172023-12-28T15:41:46Z Lightning prediction using radiosonde data Weng L.Y. Omar J.B. Siah Y.K. Abidin I.B.Z. Ahmad S.K. 26326032700 24463418200 24448864400 35606640500 25926812900 Artificial intelligence Lightning forecasting Lightning prediction Neural networks Electric load forecasting Lightning Radiosondes Back propagation neural networks C codes Kuala lumpur international airports Radiosonde datum Wind parameters Neural networks 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. Final 2023-12-28T07:41:46Z 2023-12-28T07:41:46Z 2008 Conference paper 2-s2.0-62449251537 https://www.scopus.com/inward/record.uri?eid=2-s2.0-62449251537&partnerID=40&md5=a1367a81aaa94d65392694da7314909f https://irepository.uniten.edu.my/handle/123456789/29717 78 81 Scopus
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/
topic Artificial intelligence
Lightning forecasting
Lightning prediction
Neural networks
Electric load forecasting
Lightning
Radiosondes
Back propagation neural networks
C codes
Kuala lumpur international airports
Radiosonde datum
Wind parameters
Neural networks
spellingShingle Artificial intelligence
Lightning forecasting
Lightning prediction
Neural networks
Electric load forecasting
Lightning
Radiosondes
Back propagation neural networks
C codes
Kuala lumpur international airports
Radiosonde datum
Wind parameters
Neural networks
Weng L.Y.
Omar J.B.
Siah Y.K.
Abidin I.B.Z.
Ahmad S.K.
Lightning prediction using radiosonde data
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.
author2 26326032700
author_facet 26326032700
Weng L.Y.
Omar J.B.
Siah Y.K.
Abidin I.B.Z.
Ahmad S.K.
format Conference paper
author 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 2023
_version_ 1806428036767154176
score 13.214268

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