USING DATA MINING FOR ANALYSIS OF ROAD ACCIDENTS AND PREDICTION
Sanmay Yadav
Sherwood College, Nainital, Uttarakhand, India
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In India, Streets assume a significant part in Mishaps. There are many explanations behind mishaps in India, such as drinking liquor, barometrical condition, the association focuses, vehicle issues, speed, street abandons, etc. The significant objective of this paper is to make up a scientific model for street mishaps considering prior years' datasets from 2011-2021 and anticipating the future aftereffect of 2022. The required datasets are gathered from the data.gov.in site for additional handling. A crossbreed procedure is created utilizing the information mining methods, for example, Straight Relapse, K-Means Grouping, Affiliation Rule furthermore, and Naive Bayes calculations. There are 3 components of catastrophe furthest point has been explored by estimating the result of 2022. Considering all spots and fiascos' great and low-level recurrence, the clustering of spots (states) is finished. Similarly, the proposed model yields a reasonably better precision rate.
Keywords:
data mining; road accidents; accident prediction
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