17th World Summit on Positive Psychology, Psychotherapy & Cognitive Behavioral Sciences
Toronto, Canada
Zhaoge Liu
Harbin Institute of Technology, China
Title: Big data driven indicator choosing for disaster response capacity shortage assessment of urban critical infrastructure
Biography
Biography: Zhaoge Liu
Abstract
Critical Infrastructure (CI) is a kind of complex and huge network system and its operating failure will cause serious impact on national interest. Indicators of CI disaster response capacity shortage assessment need to be systematic, objective and consistent and analyzing at the aspect of capacity shortage help us to grasp the weak spots and improve response capacity. This paper proposes a big data driven indicator choosing method for CI response capacity shortage assessment. With the big data driven method, we can obtain and grasp historical experience guiding the scenario designing and global indicator choosing of CI response capacity shortage assessment. Besides, we can identify potential basic indicators and guides the basic indicator choosing and improving by data analysis.