Lightning forecasting using ANN-BP & radiosonde

This paper presents a concept of predicting lightning with the data from radiosonde and a more reliable dataset of lightning occurances from Tenaga Nasionl Berhad Research Sdn Berhad (TNBR). The location of interest in this research is Kuala Lumpur International Airport (KLIA). The engine used for p...

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Bibliographic Details
Main Authors: Weng, L.Y., Omar, J.B., Siah, Y.K., Ahmed, S.K., Abidin, I.B.Z., Abdullah, N.
Format: Conference Paper
Language:English
Published: 2017
Online Access:http://dspace.uniten.edu.my/jspui/handle/123456789/6300
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Summary:This paper presents a concept of predicting lightning with the data from radiosonde and a more reliable dataset of lightning occurances from Tenaga Nasionl Berhad Research Sdn Berhad (TNBR). The location of interest in this research is Kuala Lumpur International Airport (KLIA). The engine used for prediction is of a Neural Network Back Propogation type (ANN-BP). The initial results show that the combination of datasets and engine are workable, however the prediction results seem to be more biased towards lightning days as compared to non-lightning days. © 2010 IEEE.