• DocumentCode
    1907983
  • Title

    Predict Time Series Data for the Number of Asthmatic Attacks in Himeji by Fuzzy-AR Model

  • Author

    Kaku, Yoshifumi ; Kuramoto, Koji ; Kobashi, Shoji ; Hata, Yuki

  • Author_Institution
    Grad. Sch. of Eng., Univ. of Hyogo, Himeji, Japan
  • fYear
    2012
  • fDate
    5-7 Nov. 2012
  • Firstpage
    314
  • Lastpage
    317
  • Abstract
    Asthma causes the bronchus inflammation, and makes breathing impossible. In worst case, asthma causes death by dyspnea. If we can predict cause asthmatic attacks, they can prevent from asthmatic attacks. Therefore, asthmatic attacks prediction system is desired. As a prediction system using time series data, there is Fuzzy-AR model that can consider multi factors. In this paper, we propose a prediction method of the number of asthmatic attacks on next month based on Fuzzy-AR model. The proposed method considers weather factors, temperature, atmospheric pressure and humidity data. This method is applied to asthmatic attacks data from Himeji city Medical Association. As a comparison method, AR model is applied to same data. The experimental results shown that the proposed method predicts the number of asthmatic attacks better than AR model.
  • Keywords
    atmospheric humidity; atmospheric pressure; atmospheric temperature; autoregressive processes; diseases; fuzzy set theory; prediction theory; time series; Himeji city Medical Association; asthmatic attack prediction system; atmospheric pressure; bronchus inflammation; dyspnea; fuzzy-AR autoregressive model; fuzzy-AR model; humidity data; prediction method; temperature data; time series data; weather factors; asthmatic attack; autoregressive model; healthcare system; time-series data;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Emerging Trends in Engineering and Technology (ICETET), 2012 Fifth International Conference on
  • Conference_Location
    Himeji
  • ISSN
    2157-0477
  • Print_ISBN
    978-1-4799-0276-7
  • Type

    conf

  • DOI
    10.1109/ICETET.2012.31
  • Filename
    6495228