Comparison of accident prediction model between ANN and MLR models
Accident rate that occurred in Malaysia has been increased for every year. Govern ment and all concern parties constantly worrying about this matter where serious measures should be taken to prevent this rising accident rate fro m happened. Therefore, a forecasting of accident prediction models h...
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| நிகழà¯à®¨à®¿à®²à¯ˆ அணà¯à®•à®²à¯: | http://eprints.uthm.edu.my/2372/ http://eprints.uthm.edu.my/2372/1/94.pdf |
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| தொகà¯à®ªà¯à®ªà¯: | Accident rate that occurred in Malaysia has been increased for every year. Govern ment and all
concern parties constantly worrying about this matter where serious measures should be taken to
prevent this rising accident rate fro m happened. Therefore, a forecasting of accident prediction
models have to be developed. In this study, the locations were focus in rural selected area. The
locations of the study were selected among the highest accident rates in Federal Route 050
based on accident point weightage analysis. Traffic volu me, speed, number of access point and
gaps data were used to develop the models. Data collections have been done through manual
observation at high risk area. The parameters were then used to develop an accident predictio n
model by using the Artificial Neural Network (ANN) and Multiple Linear Regression (MLR)
models. Both models were then utilized and MLR model was identified to give the better result
in term of reducing the number of accidents compared to ANN. Therefore, MLR model was
suggested to be used by the concern parties in order to predict the accident as to reduce the
accidents more effectively and further to achieve the national set reduction target. |
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