基于支持向量机回归的天气型家庭保险风险建模
Modeling Weather-induced Home Insurance Risks with Support Vector Machine Regression
摘要：
保险业是最易受气候变化影响的行业之一。对未来索赔数目和已发生损失的评估对于备灾和风险管理至关重要。在这个项目中，我们研究了降水对天气引起的家庭保险索赔和损失的联合动力学的影响。我们讨论的效用和限制等机器学习程序，支持向量机和人工神经网络，在预测未来的索赔动态和评估相关的不确定性。我们说明了我们的方法应用归因分析和预测天气引起的家庭保险索赔在加拿大大草原的一个中等规模的城市。
英文摘要：
Insurance industry is one of the most vulnerable sectors to climate change. Assessment of future number of claims and incurred losses is critical for disaster preparedness and risk management. In this project, we study the effect of precipitation on a joint dynamics of weather-induced home insurance claims and losses. We discuss utility and limitations of such machine learning procedures as Support Vector Machines and Artificial Neural Networks, in forecasting future claim dynamics and evaluating associated uncertainties. We illustrate our approach by application to attribution analysis and forecasting of weather-induced home insurance claims in a middle-sized city in the Canadian Prairies.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
