Abstract
This research project is about landslide prediction using back propagation neural network. The objectives of the research project are to identify rainfall variable that is used for landslide prediction, apply the back propagation neural network model to classify the risks of landslide and determine whether Back propagation Neural Network can be used as one of prediction tools. A simple threelayer neural network with six input nodes and three output nodes is employed to learn the data. Experiments are performed to determine the optimal learning. The total accuracy of prediction rate is 88.7 %. This research reveals that with a few improvements, back propagation neural network is able to be used in the prediction.
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Subjects:  Q Science > Q Science (General) > Back propagation (Artificial intelligence) Q Science > QA Mathematics > Mathematical statistics. Probabilities > Prediction analysis Q Science > QA Mathematics > Instruments and machines > Electronic computers. Computer science > Neural networks (Computer science) Q Science > QA Mathematics > Instruments and machines > Electronic computers. Computer science > Neural networks (Computer science) 

Divisions:  Faculty of Information Technology and Quantitative Sciences  
Item ID:  1736  
Uncontrolled Keywords:  Landslide prediction, Back propagation, Neural network  
Last Modified:  21 Feb 2017 08:51 
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Filename: PPb_NOOR MUNIRAH MD SAAD CS 06_5 1.pdf