A fuzzy linguistics model for job related injury risk assessment
Proceedings of the 14th annual conference on Computers and industrial engineering
The development of a method for investigating construction site accidents using fuzzy fault tree analysis
Fuzzy set theory—and its applications (3rd ed.)
Fuzzy set theory—and its applications (3rd ed.)
A course in fuzzy systems and control
A course in fuzzy systems and control
Fuzzy logic: intelligence, control, and information
Fuzzy logic: intelligence, control, and information
Fuzzy Sets and Systems: Theory and Applications
Fuzzy Sets and Systems: Theory and Applications
Information Sciences: an International Journal
A subjective methodology for safety analysis of safety requirements specifications
IEEE Transactions on Fuzzy Systems
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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.