Citation

Beriha GS, Patnaik B, Mahapatra SS, Padhee S. Expert Syst. Appl. 2012; 39(3): 3311-3323.

Copyright

(Copyright © 2012, Elsevier Publishing)

DOI

10.1016/j.eswa.2011.09.018

PMID

unavailable

Abstract

This paper presents an artificial intelligence approach for prediction of different types of accidents (fatal to minor) in an uncertain environment. Likelihood of occurrence of accidents in the work place is a random phenomenon but judicious investment in various attribute such as expenses in health care, safety training, up-gradation of tools and machinery, and expenses on safety equipment and tools may lead to reduction in accident rate. The relationship between type of accidents and investment is difficult to establish because they do not follow any predictable rule rather associate in a non-linear manner. In such situation, fuzzy logic helps to map inputs and outputs in an efficient manner for building the inference engine so that various types of accidents can be predicted. Prediction of various types of accidents helps the managers to formulate organizational policies for improving safety performance.

Language: en