Quantifying Extreme Weather Risks and Optimizing Insurance Strategies Based on the CEV-EWM Model

极端天气事件的频繁发生增加了财产保险的不确定性。为应对这一问题,本文提出了三个模型:模型I为风险与保险保护模型,通过三个子系统(灾难性、暴露度、脆弱性)和八个指标量化风险,并利用熵权法和K-Means聚类分析优化保险定价。模型II为社区发展决策模型,分析房地产开发商和社区的成本与收益,为决策提供支持。模型III为社区保护模型,使用层次分析法(AHP)评估社区地标建筑的保护措施,并通过GE矩阵进行结果可视化。Extreme weather events have increased uncertainties in property insurance. This paper proposes three models: Model I quantifies risks using eight indicators across three subsystems (catastrophic, exposure, and vulnerability) and optimizes insurance pricing with the entropy weight method and K-means clustering. Model II analyzes costs and benefits for real estate developers and communities to support decision-making. Model III assesses community landmark protection using AHP and visualizes results with the GE matrix.

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Publication Details

Journal
Statistics and Applications
Published
2025-01-01
DOI
https://doi.org/10.12677/sa.2025.146163
Primary Topic
Insurance and Financial Risk Management
Type
article
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article

Quantifying Extreme Weather Risks and Optimizing Insurance Strategies Based on the CEV-EWM Model

诺 许
Statistics and Applications
Insurance and Financial Risk Management
article

Quantifying Extreme Weather Risks and Optimizing Insurance Strategies Based on the CEV-EWM Model

诺 许
article en

Abstract

极端天气事件的频繁发生增加了财产保险的不确定性。为应对这一问题,本文提出了三个模型:模型I为风险与保险保护模型,通过三个子系统(灾难性、暴露度、脆弱性)和八个指标量化风险,并利用熵权法和K-Means聚类分析优化保险定价。模型II为社区发展决策模型,分析房地产开发商和社区的成本与收益,为决策提供支持。模型III为社区保护模型,使用层次分析法(AHP)评估社区地标建筑的保护措施,并通过GE矩阵进行结果可视化。Extreme weather events have increased uncertainties in property insurance. This paper proposes three models: Model I quantifies risks using eight indicators across three subsystems (catastrophic, exposure, and vulnerability) and optimizes insurance pricing with the entropy weight method and K-means clustering. Model II analyzes costs and benefits for real estate developers and communities to support decision-making. Model III assesses community landmark protection using AHP and visualizes results with the GE matrix.

Statistics and ApplicationsVol. 14(06)
Climate action
Openalex Percentile: Top 78%
Insurance and Financial Risk Management
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