A novel model for risk assessment of adjacent buildings in tunneling environments

This paper presents a novel model to assess the risk of adjacent buildings in tunneling environments based on Extended Cloud Model (ECM). ECM is an organic integration of Extension Theory (ET) and Cloud Model (CM), where ET is appropriately employed to flexibly expand the variable range from [0, 1] to (−∞, +∞), and CM is used to overcome the uncertainty of fuzziness and randomness during the gradation of evaluation factors. An integrated interval recognition approach to determine the boundary of risk related intervals is presented, with both actual practices and group decisions fully considered. The risk level of a specific adjacent building is assessed by the correlation to the cloud model of each risk level. A confidence indicator θ is proposed to illustrate the rationality and reliability of evaluating results. Ten buildings adjacent to Wuhan Metro Line Two (WMLT) are randomly chosen among hundreds of adjacent buildings for a case study, and the results have proved to be consistent with the actual situation. Compared with other traditional evaluation methods, ECM has been verified to be a more competitive solution with no demands on training data. The original data can be directly entered into ECM without a normalization procedure, avoiding the potential information loss. ECM can be offered as a decision support tool for the risk assessment in urban tunneling construction and worth popularizing in other similar projects.

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