In this study, we develop a novel framework to assess health risks due to heat hazards across various localities (zip codes) across the state of Maryland with the help of two commonly used indicators i.e. exposure and vulnerability. Our approach quantifies each of the two aforementioned indicators by developing their corresponding feature vectors and subsequently computes indicator-specific reference vectors that signify a high risk environment by clustering the data points at the tail-end of an empirical risk spectrum. The proposed framework circumvents the information-theoretic entropy based aggregation methods whose usage varies with different views of entropy that are subjective in nature and more importantly generalizes the notion of risk-valuation using cosine similarity with unknown reference points.

翻译：本研究开发了一种新颖的框架，利用暴露度和脆弱性两个常用指标，评估美国马里兰州不同地区（邮政编码区域）因热危害造成的健康风险。我们的方法通过构建两个指标各自对应的特征向量来量化它们，随后通过聚类经验风险谱尾端的数据点，计算表征高风险环境的指标特定参考向量。该框架规避了基于信息论熵的聚合方法，因为这些方法依赖于不同视角的熵，而熵具有主观性；更重要的是，它利用余弦相似度与未知参考点，将风险估值概念进行了推广。