Henan University of Economics and Law, Zhengzhou, China.
PLoS One. 2022 Jul 7;17(7):e0270925. doi: 10.1371/journal.pone.0270925. eCollection 2022.
Global warming has seriously affected the local climate characteristics of cities, resulting in the frequent occurrence of urban waterlogging with severe economic losses and casualties. Aiming to improve the effectiveness of disaster emergency management, we propose a novel emergency decision model embedding similarity algorithms of heterogeneous multi-attribute based on case-based reasoning. First, this paper establishes a multi-dimensional attribute system of urban waterlogging catastrophes cases based on the Wuli-Shili-Renli theory. Due to the heterogeneity of attributes of waterlogging cases, different algorithms to measure the attribute similarity are designed for crisp symbols, crisp numbers, interval numbers, fuzzy linguistic variables, and hesitant fuzzy linguistic term sets. Then, this paper combines the best-worst method with the maximal deviation method for a more reasonable weight allocation of attributes. Finally, the hybrid similarity between the historical and the target cases is obtained by aggregating attribute similarities via the weighted method. According to the given threshold value, a similar historical case set is built whose emergency measures are used to provide the reference for the target case. Additionally, a case of urban waterlogging emergency is conducted to demonstrate the applicability and effectiveness of the proposed model, which exploits historical experiences and retrieves the optimal scheme for the current disaster emergency with heterogeneous multi attributes. Consequently, the proposed model solves the problem of diverse data types to satisfy the needs of case presentation and retrieval. Compared with the existing model, it can better realize the multi-dimensional expression and fast matching of the cases.
全球变暖严重影响了城市的局地气候特征，导致城市内涝频发，造成严重的经济损失和人员伤亡。为了提高灾害应急管理的有效性，我们提出了一种基于事例推理的异构多属性相似度算法的新型应急决策模型。首先，本文基于“物理-事理-人理”理论，建立了城市内涝灾害案例的多维属性体系。由于内涝案例属性的异构性，针对离散符号、离散数值、区间数、模糊语言变量和犹豫模糊语言术语集，设计了不同的属性相似度算法来测量属性相似度。然后，本文结合最优最劣法和最大偏差法，对属性进行更合理的权重分配。最后，通过加权方法对属性相似度进行聚合，得到历史案例和目标案例之间的混合相似度。根据给定的阈值，构建一个相似的历史案例集，其应急措施可用于为目标案例提供参考。此外，还进行了一个城市内涝应急案例，以验证所提出模型的适用性和有效性，该模型利用历史经验并检索具有异构多属性的当前灾害应急的最佳方案。因此，所提出的模型解决了不同数据类型的问题，满足了案例呈现和检索的需求。与现有模型相比，它可以更好地实现案例的多维表达和快速匹配。
