Research on cloud model of risk assessment of urban underground
diseases based on dynamic tracking and set pair theory
Research on cloud model of risk assessment of urban underground
diseases based on dynamic tracking and set pair theory
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Graphical Abstract
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Abstract
A cloud model for the risk assessment of urban underground diseases was proposed by integrating dynamic tracking theory and set pair analysis theoryFirstly，taking into account the dynamic development characteristics of diseases，a risk assessment method based on dynamic tracking thoughts was proposed by including the change rate of disease properties into risk assessment systemSecondly，assessment indicators were transformed into indicator clouds by inverse Gauss cloud algorithm based on the secondorder and fourthorder center distance，and the least squares method was used to combine and optimize the subjective cloud weight and objective critic weight to distribute weights for indicators scientificallyFinally，by introducing the set pair analysis theory，the “3En” rule of Gauss cloud model was combined with the set pair potential in set pair theory to calculate similarity of the cloud model and improve the accuracy of risk level discriminationThrough the underground disease detection project in Guiyang City and the East Fourth Ring of Beijing，the model proposed was compared with the other three assessment models and actual excavation results were used to verify the validity of the model
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