An improved Dempster-Shafer approach to construction safety risk perception

This paper proposes a novel hybrid approach that merges fuzzy matter element (FME), Monte Carlo (MC) simulation technique, and Dempster-Shafer (D-S) evidence theory to perceive the risk magnitude of tunnel-induced building damage at an early construction stage. The membership measurement in FME is used to construct basic probability assignments (BPAs) of influential factors within different risk states. An improved evidence fusion rule that integrates the Dempster' rule and the weighted average rule is developed to synthesize multi-source conflicting evidence. A new defuzzification method, Centre of Distribution (COD), is proposed to achieve a crisp value that represents the final safety risk perception result. A confidence indicator, 8, is put forward to measure the reliability of the safety risk perception result. A comprehensive information fusion framework that incorporates 14 influential factors is proposed to perceive the risk magnitude of tunnel-induced building damage. Six existing buildings adjacent to the excavation of Wuhan Yangtze Metro Tunnel (WYMT), China, are utilized as a case study to verify the effectiveness and applicability of the proposed approach. Results indicate that the proposed approach is capable of (i) achieving a more accurate result for safety risk perception, and (ii) identifying global sensitivities of input factors throughout a series of MC simulation enabled iterations. A discussion on how to define a reasonable membership function for configuration of BPAs is further presented. The authors recommend that the constant coefficient lambda that affects the shape of the defined correlation function in BPA (Basic Probability Assignment) constructs should have a value of three, and the risk perception result can thus reach up to the highest reliability level. This approach can enable a comprehensive preliminary safety risk perception during tunnel design phases, which can further substantially reduce the risk of building damage induced by tunneling excavation. (C) 2017 Elsevier B.V. All rights reserved.