NDLI: Forecast of Cerebral Infraction Incidence Rate Based on BP Neural Network and ARIMA Combined Model

Content Provider	IEEE Xplore Digital Library
Author	Fu Peng Tian Liang Liang Ma
Copyright Year	2010
Abstract	Objective Forecast and analysis of cerebral infraction incidence rate are the basis and key work of cerebral infraction prevention and control. At present, forecast of cerebral infraction incidence rate is mainly based on traditional research approach or single artificial neural network technology. Recent study results show that combined forecast model approach enjoys more precise forecast than monomial forecast approach. Methods The paper proposes a new forecast approach based on BP neural network and ARIMA combined mode and makes comprehensive analysis and forecast of the changing trend of cerebral infraction incidence rate in Haixizhou region, Qinghai province of China. Results Forecast results indicate that this approach is more precise in terms of monomial forecast method. Conclusion The combined model is feasible and effective in the forecast of cerebral infraction incidence rate.
Starting Page	216
Ending Page	219
File Size	405251
Page Count	4
File Format	PDF
ISBN	9781424481484
DOI	10.1109/IPTC.2010.7
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-10-28
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Biological system modeling Neurons Time series analysis Artificial neural networks Predictive models Data models Biological neural networks
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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