A novel multi-source information fusion method for emergency spatial resilience assessment based on Dempster-Shafer theory

IF 8.1 1区 计算机科学 0 COMPUTER SCIENCE, INFORMATION SYSTEMS Information Sciences Pub Date : 2024-08-22 DOI:10.1016/j.ins.2024.121373
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Abstract

In the midst of today's intricate and ever-changing natural and social landscape, this study is committed to proposing a novel multi-source information fusion method for assessing the spatial resilience of urban emergency evacuation and rescue. Its overarching aim is to uncover latent challenges and contribute to the enhancement of a city's capacity to respond to emergencies. To achieve this, we have devised a comprehensive assessment indicator system, capable of not only quantifying a city's spatial resilience but also offering indispensable guidance for urban emergency evacuation and rescue spatial planning. Furthermore, we have introduced an innovative evaluation methodology framework. This framework includes the establishment of the basic probability assignment (BPA) model, a pioneering method for generating BPA for observed values, and the novel application of hierarchical weighting and fusion techniques. By extending the Dempster-Shafer theory, we have not only enhanced the method's ability to express and integrate uncertain information but also significantly improved the precision of the evaluation. Ultimately, we conducted a quantitative assessment using Shenzhen, China, as a case study, identifying existing issues and proposing highly-targeted improvement strategies. These research findings not only provide robust support for the augmentation of urban emergency capabilities in Shenzhen but also offer pioneering insights for the quantitative assessment and advancement of emergency spatial resilience in cities across the globe.

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基于 Dempster-Shafer 理论的多源信息融合应急空间复原力评估新方法
在当今错综复杂、瞬息万变的自然和社会环境中,本研究致力于提出一种新颖的多源信息融合方法,用于评估城市紧急疏散和救援的空间弹性。其总体目标是发现潜在的挑战,为提高城市应对紧急情况的能力做出贡献。为此,我们设计了一套综合评估指标体系,不仅能够量化城市的空间弹性,还能为城市应急疏散和救援空间规划提供不可或缺的指导。此外,我们还引入了创新的评估方法框架。该框架包括基本概率赋值(BPA)模型的建立、为观测值生成 BPA 的开创性方法,以及分层加权和融合技术的新颖应用。通过扩展 Dempster-Shafer 理论,我们不仅增强了该方法表达和整合不确定信息的能力,还显著提高了评估的精确度。最终,我们以中国深圳为案例进行了量化评估,找出了存在的问题,并提出了针对性很强的改进策略。这些研究成果不仅为深圳城市应急能力的提升提供了有力支持,也为全球城市空间应急复原力的定量评估和提升提供了开创性的见解。
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来源期刊
Information Sciences
Information Sciences 工程技术-计算机:信息系统
CiteScore
14.00
自引率
17.30%
发文量
1322
审稿时长
10.4 months
期刊介绍: Informatics and Computer Science Intelligent Systems Applications is an esteemed international journal that focuses on publishing original and creative research findings in the field of information sciences. We also feature a limited number of timely tutorial and surveying contributions. Our journal aims to cater to a diverse audience, including researchers, developers, managers, strategic planners, graduate students, and anyone interested in staying up-to-date with cutting-edge research in information science, knowledge engineering, and intelligent systems. While readers are expected to share a common interest in information science, they come from varying backgrounds such as engineering, mathematics, statistics, physics, computer science, cell biology, molecular biology, management science, cognitive science, neurobiology, behavioral sciences, and biochemistry.
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