Traffic accidents are a problem confronted by means of each a around the arena, Indonesia isn't any exception. The Indonesian national Police recorded an increase inside the number of traffic accidents in 2019 in comparison to 2018. based totally on POLRI information, there had been 107,500 traffic accidents in 2019, an increase from 103,672 incidents in 2018. in particular in Jakarta, that is the capital city of the Republic of Indonesia, traffic accidents are a common phenomenon, in conjunction with the unexpectedly developing use of motorized motors on the dual carriageway. for that reason, a examine is wanted to determine the variety of traffic accidents with the intention to occur in the future. The observe will forecast the number of traffic accidents for every month based totally on datasets from 2015 to 2020 from the Jakarta Metro Jaya Police Traffic Directorate. The approach used on this examine makes use of facts mining methods by using comparing the artificial Neural community Backpropagation, Deep getting to know and Linear Regression algorithms to decide which algorithm is right for predicting the range of traffic injuries inside the Jakarta region in each following month. This examine concludes that the synthetic Neural community Backpropagation set of rules is the first-rate set of rules to be applied in predicting the number of visitors accidents within the Jakarta vicinity with a Root suggest square mistakes (RMSE) of 29.477. studies trying out with the aid of applying the synthetic Neural network Backpropagation algorithm version has verified to expose the price of forecasting the number of traffic accidents in Jakarta with a mean monthly accuracy cost of 97.34%.
Forecasting the Number of Traffic Accidents in Jakarta Using Artificial Neural Network
2023-12-01
612841 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
Artificial Intelligence and Forecasting of Traffic Accidents Using GIS
Springer Verlag | 2023
|Investigating and forecasting traffic accidents
Engineering Index Backfile | 1957
A model for forecasting traffic accidents
Elsevier | 1969
|Modeling and forecasting traffic accidents of Korea
British Library Conference Proceedings | 1996
|