Lightning Forecasting Modelling Using Artificial Neural Network (ANN): Case Study Sultan Abdul Aziz Shah Airport or Skypark Subang

Abstract

Lightning is one of extreme weather phenomenon in Malaysia. It is because Malaysia has high lightning and thunderstorm occurrences in yearly basis. In aviation industry, weather awareness is very important to ensure the passenger safety. Therefore, lightning forecasting is very important to warn people on lightning occurring nearby and give them an ample time to evacuate before the lightning happens. Thus, this paper proposed lightning forecasting using Artificial Neural Network (ANN) at Sultan Abdul Aziz Shah Airport Subang. The ANN model developed using Multilayer Perceptron Neural Network (MLPNN) structure and then the simulation result is compared with the actual values. Data used is meteorological data obtained from Meteorological Malaysian Services (MMS). Simulation is done using Matlab Neural Network Toolbox for training and testing process. Simulation results showed that MLPNN successfully predict the occurrence of lightning ahead of time in Sultan Abdul Aziz Shah Airport Subang.