Advances in Machine Learning & Artificial Intelligence(AMLAI)

Faculty Civil Engineering Technology, Universiti Malaysia Pahang Al-Sultan Abdullah, Malaysia

Publications

• Research Article   
  Machine Learning Based on Neural Network Fitting for Traffic Behaviour at Road Intersection in Mixed Traffic Condition
  Author(s): Fajaruddin Mustakim*, Azlan Abdul Aziz, Lim Heng Siong, Yaser Bakhuraisa, Othman Che Puan, Mohammad Nazir Ahmad, Rabiah Abdul Kadir and Riza Sulaiman
  
  Artificial Neural Networks (ANNs) play an essential role in artificial intelligence to explore and simulate the traffic behaviour on road network safety. In this study, eight cluster as input variables and one output were utilize to simulate the performance of the model. Input predictors involved traffic of conflict, vehicle category, second vehicles passing right turn motor vehicles (RMV), first vehicles passing (RMV), speed limit, gap pattern, day time, and infrastructure. Meanwhile output variables were right turn motor vehicles (RMV). Neural Network Fitting apply as the Machine Learning has been implemented to measure the mean square error and the regression value. The network was trained with eight hundred and forty-one datasets has been collected on mix traffic condition. Neural Network Fitting consist three approaches to trained the datasets namely Levenberg- Marquardt Algorith.. Read More»
  

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