• Nagendra Babu S
• Dr.J. Jebamalar Tamilselvi,

Lately, the accident rate identified with activity is high. Investigating the accident information and separating valuable data from it can help in taking individual measures to diminish this rate or keep the accident from happening. Related research has been done in the past which included proposing different measures and algorithms to get intriguing accident designs from the accident records. The primary issue is that expansive quantities of examples were delivered and huge number of these examples would be evident or not fascinating. A more profound investigation of the information is required keeping in mind the end goal to get the intriguing examples. With a specific end goal to conquer this circumstance, we have proposed another way to deal with distinguish the most related successive examples in the accident information. We likewise influence utilization of the procedure.The principle objective of this paper is to identify the most related successive examples (MASP) and mine different data examples inside the informational collections produced by MASP utilizing an adjusted FP-growth approach in standard affiliation mining. This paper proposed a new Improved Association Rule Mining(IARM) algorithm for the prediction of road accidents and proposing suggestion to higher authorities for increasing safety measures on highways.

Association rule mining;accident data;information mining;rule based mining

"Association Rule mining for Road Accident Prediction Using IARM Algorithm", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 4, page no.1085-1088, April-2018, Available :http://www.jetir.org/papers/JETIR1804217.pdf

"Association Rule mining for Road Accident Prediction Using IARM Algorithm", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 4, page no. pp1085-1088, April-2018, Available at : http://www.jetir.org/papers/JETIR1804217.pdf