Yimin Yang, Daniel Lopez, Haiman Tian, Samira Pouyanfar, Fausto Fleites, Shu‐Ching Chen, S. Hamid
{"title":"Integrated execution framework for catastrophe modeling","authors":"Yimin Yang, Daniel Lopez, Haiman Tian, Samira Pouyanfar, Fausto Fleites, Shu‐Ching Chen, S. Hamid","doi":"10.1109/ICOSC.2015.7050807","DOIUrl":null,"url":null,"abstract":"Home insurance is a critical issue in the state of Florida, considering that residential properties are exposed to hurricane risk each year. To assess hurricane risk and project insured losses, the Florida Public Hurricane Loss Model (FPHLM) funded by the states insurance regulatory agency was developed. The FPHLM is an open and public model that offers an integrated complex computing framework that can be described in two phases: execution and validation. In the execution phase, all major components of FPHLM (i.e., data pre-processing, Wind Speed Correction (WSC), and Insurance Loss Model (ILM)) are seamlessly integrated and sequentially carried out by following a coordination workflow, where each component is modeled as an execution element governed by the centralized data-transfer element. In the validation phase, semantic rules provided by domain experts for individual component are applied to verify the validity of model output. This paper presents how the model efficiently incorporates the various components from multiple disciplines in an integrated execution framework to address the challenges that make the FPHLM unique.","PeriodicalId":126701,"journal":{"name":"Proceedings of the 2015 IEEE 9th International Conference on Semantic Computing (IEEE ICSC 2015)","volume":"96 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2015 IEEE 9th International Conference on Semantic Computing (IEEE ICSC 2015)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICOSC.2015.7050807","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
Home insurance is a critical issue in the state of Florida, considering that residential properties are exposed to hurricane risk each year. To assess hurricane risk and project insured losses, the Florida Public Hurricane Loss Model (FPHLM) funded by the states insurance regulatory agency was developed. The FPHLM is an open and public model that offers an integrated complex computing framework that can be described in two phases: execution and validation. In the execution phase, all major components of FPHLM (i.e., data pre-processing, Wind Speed Correction (WSC), and Insurance Loss Model (ILM)) are seamlessly integrated and sequentially carried out by following a coordination workflow, where each component is modeled as an execution element governed by the centralized data-transfer element. In the validation phase, semantic rules provided by domain experts for individual component are applied to verify the validity of model output. This paper presents how the model efficiently incorporates the various components from multiple disciplines in an integrated execution framework to address the challenges that make the FPHLM unique.