Lightning Forecasting Using Ann-BP and Radiosonde
Leong Yeng Weng, Jamaludin Bin Omar, Yap Keem Siah, Syed Khaleel Ahmed, Izham Zainal Abidin, Noradlina Abdullah · 2010
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.