基于空间代理的台风期间抢先疏散决策模型
A Spatial Agent-Based Model for Preemptive Evacuation Decisions During Typhoon
摘要：
自然灾害继续给人类生命和财产造成巨大损害。由于其地理位置，菲律宾被认为是一个自然灾害多发国家，平均每年经历20次热带气旋。了解哪些因素在关键疏散阶段对决策产生重大影响，有助于决策如何做好灾害准备，如何在灾害期间和灾害后采取适当和战略性的行动。在这项工作中，基于Agent的模型，在台风期间先发制人的疏散决策。在该模型中，平民代表的家庭和他们的疏散决定的基础上计算的感知风险。此外，救援人员和避难所管理人员在先发制人的疏散过程中被列为促进者。该模型采用了国家和市政人口普查数据，特别是家庭代理人的人口统计数据。此外，一个村庄的地理空间数据在台风易感的城市被用来代表环境。撤离或不撤离的决定取决于代理人的感知风险，这也取决于三个决策因素：决策者的特征（CDM）;容量相关因素（CRF）;和危险相关因素（HRF）。最后，在模拟过程中确定了受模型决策因素影响的决定撤离或选择留下的家庭数量。线性回归的敏感性分析表明，模型中使用的所有参数是显着的家庭代理人的疏散决策。
英文摘要：
Natural disasters continue to cause tremendous damage to human lives and properties. The Philippines, due to its geographic location, is considered a natural disaster-prone country experiencing an average of 20 tropical cyclones annually. Understanding what factors significantly affect decision making during crucial evacuation stages could help in making decisions on how to prepare for disasters, how to act appropriately and strategically respond during and after a calamity. In this work, an agent-based model for preemptive evacuation decisions during typhoon is presented. In the model, civilians are represented by households and their evacuation decisions were based from calculated perceived risk. Also, rescuer and shelter manager agents were included as facilitators during the preemptive evacuation process. National and municipal census data were employed in the model, particularly for the demographics of household agents. Further, geospatial data of a village in a typhoon-susceptible municipality was used to represent the environment. The decision to evacuate or not to evacuate depends on the agent's perceived risk which also depends on three decision factors: characteristics of the decision maker (CDM); capacity related factors (CRF); and hazard related factors (HRF). Finally, the number of households who decided to evacuate or opted to stay as influenced by the model`s decision factors were determined during simulations. Sensitivity analysis using linear regression shows that all parameters used in the model are significant in the evacuation decision of household agents.
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