scholarly journals Using GUHA Data Mining Method in Analyzing Road Traffic Accidents Occurred in the Years 2004–2008 in Finland

2017 ◽  
Vol 2 (3) ◽  
pp. 224-231 ◽  
Author(s):  
Esko Turunen
Keyword(s):  
Data Mining ◽  
Traffic Accidents ◽  
Road Traffic ◽  
Mining Method ◽  
Road Traffic Accidents ◽  
Data Mining Method

scholarly journals Empirical Modelling for exploring the factors contributing to disability severity from road traffic accidents in Thailand

1970 ◽  
Vol 6 (2) ◽  
pp. 176-185
Author(s):  
Jaratsri Rungrattanaubol ◽  
Anamai Na-udom ◽  
Antony Harfield
Keyword(s):  
Neural Network ◽  
Data Mining ◽  
Traffic Accidents ◽  
Injury Severity ◽  
Road Traffic ◽  
Road Traffic Accidents ◽  
Empirical Modelling ◽  
Standard Data ◽  
Accident Data ◽  
Computer Based

This paper introduces a computer-based model for predicting the severity of injuries in road traffic accidents. Using accident data from surveys at hospitals in Thailand, standard data mining techniques were applied to train and test a multilayer perceptron neural network. The resulting neural network specification was loaded into an interactive environment called EDEN that enables further exploration of the computer-based model. Although the model can be used for the classification of accident data in terms of injury severity (in a similar way to other data mining tools), the EDEN tool enables deeper exploration of the underlying factors that might affect injury severity in road traffic accidents. The aim of this paper is to describe the development of the computer-based model and to demonstrate the potential of EDEN as an interactive tool for knowledge discovery.

scholarly journals Road Traffic Accidents Analysis Using Data Mining Techniques

2018 ◽  
Vol 14 (2) ◽  
Author(s):  
G. Janani ◽  
N. Ramya Devi
Keyword(s):  
Data Mining ◽  
Association Rule ◽  
Association Rule Mining ◽  
Traffic Accidents ◽  
Road Traffic ◽  
Road Accident ◽  
Road Traffic Accidents ◽  
Road Accidents ◽  
Rule Mining ◽  
Data Mining Techniques

Road Traffic Accidents (RTAs) are a major public concern, resulting in an estimated 1.2 million deaths and 50 million injuries worldwide each year. In the developing world, RTAs are among the leading cause of death and injury. Most of the analysis of road accident uses data mining techniques which provide productive results. The analysis of the accident locations can help in identifying certain road accident features that make a road accident to occur frequently in the locations. Association rule mining is one of the popular data mining techniques that identify the correlation in various attributes of road accident. Data analysis has the capability to identify different reasons behind road accidents. In the existing system, k-means algorithm is applied to group the accident locations into three clusters. Then the association rule mining is used to characterize the locations. Most state of the art traffic management and information systems focus on data analysis and very few have been done in the sense of classification. So, the proposed system uses classification technique to predict the severity of the accident which will bring out the factors behind road accidents that occurred and a predictive model is constructed using fuzzy logic to predict the location wise accident frequency.

scholarly journals Using Decision Tree Data Mining Algorithm to Predict Causes of Road Traffic Accidents, its Prone Locations and Time along Kano –Wudil Highway

2017 ◽  
Vol 10 (1) ◽  
pp. 197-206 ◽  
Author(s):  
L. J. Muhammad ◽  
Sani Salisu ◽  
Atomsa Yakubu ◽  
Yusuf Musa Malgwi ◽  
Elrufai Tijjani Abdullahi ◽  
...  
Keyword(s):  
Data Mining ◽  
Decision Tree ◽  
Traffic Accidents ◽  
Road Traffic ◽  
Data Mining Algorithm ◽  
Road Traffic Accidents ◽  
Mining Algorithm ◽  
Tree Data

A Study on Detection of Small Size Malicious Code using Data Mining Method

2019 ◽  
Vol 19 (1) ◽  
pp. 11-17
Author(s):  
Taek-Hyun Lee ◽  
◽  
Ho Kook Kwang
Keyword(s):  
Data Mining ◽  
Malicious Code ◽  
Mining Method ◽  
Data Mining Method ◽  
Using Data

ADHD is a Risk Factor of Road Crashes: A Purposive Study of Finding Relation between ADHD and Road Traffic Accident in Bangladesh

2018 ◽  
Vol 9 (08) ◽  
pp. 20531-20536
Author(s):  
Nusrat Shamima Nur ◽  
M. S. l. Mullick ◽  
Ahmed Hossain
Keyword(s):  
Risk Factor ◽  
Road Traffic Accident ◽  
Traffic Accident ◽  
Traffic Accidents ◽  
Road Traffic ◽  
Fatality Rate ◽  
Road Traffic Accidents ◽  
Road Crashes ◽  
Road Crash ◽  
Day By Day

Background: In Bangladesh fatality rate due to road traffic accidents is rising sharply day by day. At least 2297 people were killed and 5480 were injured in road traffic accidents within 1st six months of 2017.Whereas in the previous year at 2016 at least 1941 people were killed and 4794 were injured within the 1st six months. No survey has been reported in Bangladesh yet correlating ADHD as a reason of impulsive driving which ends up in a road crash.

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