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Title: Prediction of rainfall intensity using artificial intelligence (AI) techniques in Singapore
Authors: Toh, Jia Yee
Keywords: DRNTU::Engineering::Electrical and electronic engineering
Issue Date: 2019
Abstract: This paper will be covering the usage of artificial intelligence techniques, mainly using non-linear autoregressive with external(exogenous) input (NARX) to predict rainfall intensity in Singapore some 5, 15 and 30 minutes intervals ahead. The time-series data will be analysed by using data mining techniques. Then, it will be grouped into four different on and off monsoon seasons, which are later used as training data for different artificial neural networks. Different scenarios of neural network will be explored using MATLAB NARX to find the best accuracy for predicting the intensity of the rainfall events.
Schools: School of Electrical and Electronic Engineering 
Rights: Nanyang Technological University
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:EEE Student Reports (FYP/IA/PA/PI)

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