Data analysis in road accidents using ann and decision tree

Title

Data analysis in road accidents using ann and decision tree

Creator

Kumar R.R.; Ramamurthy B.

Description

Road accidents have become some of the main causes for fatal death globally. A report tells that road accident is the major cause for high death rate other than wars and diseases. A study by World Health Organization (WHO), Global status report on road safety 2015 says over 1.24 million people die every year due to road accidents worldwide and it even predicts by 2020 this number can even increase by 20-50%. This can affect the GDP of the Country, for developing countries this can affect adversely. This paper shows the use of data analytics techniques to build a prediction model for road accidents, so that these models can be used in real time scenario to make some policies and avoid accidents. This paper has identified the attributes which has high impact on accident severity class label. IAEME Publication.

Source

International Journal of Civil Engineering and Technology, Vol-9, No. 4, pp. 214-221.

Date

2018-01-01

Publisher

IAEME Publication

Subject

ANN; Back Propagation.; Data analysis; Decision tree; Machine learning; Prediction/Classification; Road accident

Coverage

Kumar R.R., Department of Computer Science, CHRIST (Deemed to be University), Bengaluru, India; Ramamurthy B., Department of Computer Science, CHRIST (Deemed to be University), Bengaluru, India

Rights

Restricted Access

Relation

ISSN: 9766308

Format

Online

Language

English

Type

Article

Identifier

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85046342997&partnerID=40&md5=e9b57b989179aa139757c1c21045e75b