Main Article Content
Roadway traffic safety is a major concern for transportation governing agencies as well as ordinary citizens.Data Mining is taking out of hidden patterns from huge database. It is commonly used in a marketing, surveillance, fraud detection and scientific discovery. In data mining, machine learning is mainly focused as research which is automatically learnt to recognize complex patterns and make intelligent decisions based on data. Globalization has affected many countries. There has been a drastic increase in the economic activities and consumption level, leading to expansion of travel and transportation. The increase in the vehicles, traffic lead to road accidents. Considering the importance of the road safety, government is trying to identify the causes of road accidents to reduce the accidents level. The exponential increase in the accidents data is making it difficult to analyse the constraints causing the road accidents. The paper describes how to mine frequent patterns causing road accidents from collected data set. We find associations among road accidents and predict the type of accidents for existing as well as for new roads. We make use of association and classification rules to discover the patterns between road accidents and as well as predict road accidents for new roads.
How to Cite
, N. A. P. A. D. G. (2018). Roadway Traffic Analysis using Data Mining Techniques for Providing Safety Measures to Avoid Fatal Accidents. International Journal on Future Revolution in Computer Science &Amp; Communication Engineering, 4(6), 45–50. Retrieved from https://ijfrcsce.org/index.php/ijfrcsce/article/view/1684