基于“风险源+承灾体+减灾体”的城市安全表征“库-网-流-谱-法”理论框架

我国的城市安全面临自然灾害、事故灾难等多种重大挑战。针对城市安全现阶段的实际需求与重要难题，该研究引入“减灾体”和“减灾力”的概念，以风险源、承灾体和减灾体为三大基本要素，依托数字孪生、机器学习、知识图谱等新技术，建立了基于“风险源+承灾体+减灾体”的城市安全表征“库-网-流-谱-法”理论框架，并对该框架中每个环节涉及的研究内容与关键问题进行了详细阐述。所提出的理论有望更加合理地表征城市的管理能力在城市安全中的作用，助力实现城市安全性态的动态表征以及相关决策的智能学习与优化。

THE "DATABASE-NETWORK-FLOW-SPECTRUM-LAW" THEORETICAL FRAMEWORK FOR URBAN SAFETY CHARACTERIZATION BASED ON "RISK SOURCE" + "RISK EXPOSURE" + "MITIGATION FACTOR"

The urban safety in China is faced with many major challenges such as natural disasters and incidents. To meet the practical needs and to solve the important issues in urban safety at the current stage, the theoretical framework for characterization of urban safety is proposed. First, the concepts of "mitigation factor" and "mitigation capacity" are introduced into the framework. Then, taking the so-called "risk source", "risk exposure" and "mitigation factor" as the fundamental components, the Database-Network-Flow-Spectrum-Law theoretical framework is proposed, in which the advantages of new technologies (e.g., digital twin, knowledge graph and machine learning) are considered. The concept and key issues of the five stages of the framework are elaborated. The proposed theory is expected to characterize the capability of city managers in urban safety more reasonably, to help realizing the dynamic characterization of urban safety performance, and to provide an intelligent learning approach and an optimization method for management decisions.