Development of an intelligent knowledge base for identification of accident causes based on Fu et al.'s model - (:unkn) unknown (TAYLOR & FRANCIS LTD, 2022)
In this study, an intelligent knowledge base (IKB) is developed based on a model developed by Fu et al. for identification of accident causes, which may play a significant role in preventing accidents. This IKB has been generated using eight sample accidents reported in the literature and tested by two additional accidents. The causes of these sample accidents were identified according to a model taxonomy developed by Fu et al. For the test, an oil spill and a refinery accident are considered in two case studies. This study proved 89.47 and 73.01% success rates, respectively, for the identification of additional accidents causes based on the developed IKB. These results obtained from only eight sample accidents are considered promising because as the number of sample accidents increases, the success rates are expected to increase further. This IKB was prepared as part of a more comprehensive intelligent system to be developed.
Keywords: intelligent knowledge base; accident causation models; occupational accidents; accident analysis; DEFENSE-IN-DEPTH; EXPERT-SYSTEM; POWER-PLANT; DIAGNOSABILITY; STAMP