Domain knowledge assisted data processing for Florida public hurricane loss model

Yilin Yan, Samira Pouyanfar, Haiman Tian, Sheng Guan, Hsin Yu Ha, Shu Ching Chen, Mei-Ling Shyu, Shahid Hamid

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

Catastrophes have caused tremendous damages in human history and triggered record high post-disaster relief from the governments. The research of catastrophic modeling can help estimate the effects of natural disasters like hurricanes, floods, surges, and earthquakes. In every Atlantic hurricane season, the state of Florida in the United States has the potential to suffer economic and human losses from hurricanes. The Florida Public Hurricane Loss Model (FPHLM), funded by the Florida Office of Insurance Regulation, has assisted Florida and the residential insurance industry for more than a decade. How to process big data for historical hurricanes and insurance companies remains a challenging research topic for cat models. In this paper, the FPHLMs novel integrated domain knowledge assisted big data processing system is introduced and its effectiveness of data processing error prevention is presented.

Original languageEnglish (US)
Title of host publicationProceedings - 2016 IEEE 17th International Conference on Information Reuse and Integration, IRI 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages441-447
Number of pages7
ISBN (Electronic)9781509032075
DOIs
StatePublished - 2016
Event17th IEEE International Conference on Information Reuse and Integration, IRI 2016 - Pittsburgh, United States
Duration: Jul 28 2016Jul 30 2016

Other

Other17th IEEE International Conference on Information Reuse and Integration, IRI 2016
CountryUnited States
CityPittsburgh
Period7/28/167/30/16

Keywords

  • Big Data Processing
  • Catastrophe Modeling
  • Florida Public Hurricane Loss Model (FPHLM)
  • Post-processing
  • Pre-processing

ASJC Scopus subject areas

  • Information Systems
  • Information Systems and Management

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  • Cite this

    Yan, Y., Pouyanfar, S., Tian, H., Guan, S., Ha, H. Y., Chen, S. C., Shyu, M-L., & Hamid, S. (2016). Domain knowledge assisted data processing for Florida public hurricane loss model. In Proceedings - 2016 IEEE 17th International Conference on Information Reuse and Integration, IRI 2016 (pp. 441-447). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IRI.2016.65