Abstract
Jabatan Pengangkutan Jalan Malaysia (JPJ) is one of government constitution that is responsible in managing all aspects regarding to the vehicles that are using the road in Malaysia such as vehicles registration, road tax and traffic rules. Total registered vehicles in Malaysia are uncertain and differ according to state. Due to these,the JPJ faces problems in predicting the numbers of vehicle registered in the future. Approximation of total registered vehicles in the next few months will only be made based on historical data. These usually give an inaccurate result. Thus, the new vehicles registration forecasting models are developed to forecast the number of new vehicles registration in Malaysia for next 12 months. There are 4 models that are developed which are model for Johor, Kuala Lumpur, Pulau Pinang and Malaysia. These models are developed using Neural Network with Back Propagation algorithm and MATLAB 7.0 software package. Hopefully these models can contribute an efficient and accurate result in order to help the JPJ to solve problems and improve their management.
Website : http://ir.fsksm.utm.my/1066/
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