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
Link To Document :
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