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A multi-agent-based model for sustainable governance of urban flood risk mitigation measures

机译:城市洪水风险减缓措施的可持续治理基于多智能经理模型

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摘要

Consequences of urban floods increased and diversified in terms of social, economical and environmental effects, due to the dense and unplanned urbanization in areas at risk of flooding. Reducing the potential damage of flood is one of the most effective and sustainable reduction strategies of flood risks through adopting adequate urban flood risk mitigation measures (UFRM). The main objective of this study is to ascertain urban floods and develop a model identifying UFRM in accordance with their importance in reducing the effects of floods by employing the concept of multi-agent systems. Social, economical and environmental-based agents were modelled in the agent environment to consider the three dimensions of sustainability in the proposed model. Thirteen negotiation strategies were developed for the agents to negotiate with each other. An illustrative case study was then performed to test the proposed model features, and the results were thoroughly analysed. Sensitivity analysis was conducted to specify the most sensitive strategies over the changing fuzziness level of agents. It was observed that the best strategy differs with respect to short-, medium- and long-term gains significantly, which, in turn, lead to alterations in the list of UFRM. This could provide different risk mitigation plans for different regions with their changing resources. In summary, this study provides an innovative multi-agent-based model that can be performed to specify the most urgent UFRM which can be used by disaster coordination and management authorities as a decision-making input.
机译:由于洪水风险风险的地区,城市洪水的后果在社会,经济和环境影响方面增加和多样化。通过采用充足的城市洪水风险缓解措施(UFRM),降低洪水潜在损害是洪水风险最有效和可持续的策略之一。本研究的主要目标是确定城市洪水,并根据凭借多委托系统的概念来减少洪水影响的重要性,开发鉴定ufrm的模型。社会,经济和环境的代理商在代理环境中进行了建模,以考虑拟议模型中可持续性的三个维度。为代理商而开设了十三次谈判策略,互相谈判。然后进行说明性案例研究以测试所提出的模型特征,并彻底分析了结果。进行了敏感性分析,以指定更敏感的策略,这些策略在变化的代理商的模糊水平上。据观察,最佳策略与短期,中期和长期收益显着不同,反过来又导致UFRM列表中的改变。这可以为不同地区提供不同地区的不同风险缓解计划。总之,本研究提供了一种基于创新的多代理的模型,可以执行以指定最迫切的UFRM,该模型可以被灾害协调和管理权限用作决策输入。

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