A state-of-the-art survey on neural computation-enhanced Dempster–Shafer theory for safety accidents: Applications, challenges, and future directions

Abstract

Frequent workplace accidents associated with rapid industrialization has become the global focus. Such accidents not only pose a serious threat to the safety and health of employees but can also incur substantial economic losses and reputational damage for companies. Therefore, determining ways to effectively reduce workplace accidents and their possibilities has become an urgent problem that needs to be solved. In the field of safety management, numerous scholars and practitioners are committed to researching and applying various theories and methods to improve workplace safety. Recently, the Dempster–Shafer theory (DST) has garnered attention an important uncertainty reasoning method in the field of safety management. By integrating information from multiple sources, the theory can make effective reasoning using uncertain or incomplete information and provide strong support for safety management decision-making. Recently, neural computation techniques have been explored to enhance the reasoning capabilities of DST, enabling more efficient fusion and analysis of complex and high-dimensional safety data. In view of this, this study systematically reviews relevant papers on DST in the field of safety, accident, and emergency management and forms a systematic literature review (SLR). To support and guide the completion of this work, this paper proposes three research questions based on the 4R crisis management theoretical framework. On the same theoretical basis, the selected literature is sorted and analyzed according to the four dimensions of $Reduction$, $Readiness$, $Response$ and $Recovery$, covering all aspects of these dimensions; moreover, the results are obtained through SLR. The final results show that DST enhanced with neural computation plays vital roles in the field of safety, accident, and emergency management. This coupling reduces the limitations of DST, expanding its scope in the process. However, several limitations remain to be solved. Accordingly, this paper analyzes ways to solve the extended theory, practical application dimension, and related defects of DST in the field of safety, accident, and emergency management and draws some conclusions.