An Alarming and Prediction System for Infections Disease Based on Combined Models
With the continuous improvement of the economy and the medical technology, people’s living conditions and sanitation facilities have been greatly improved. However, the human infectious disease with a higher prevalence can cause sudden public health incidents. They are more difficult to control and can easily cause public panic disorders. Early identification of infectious disease out breaks and takes prompt and effective measures in a timely, and can greatly reduce morbidity and mortality of infectious disease and loss of property. Therefore, the monitoring of infectious disease, early detection of infectious disease outbreaks of dangerous diseases to make early alarming and prediction is the focus of attention and research. Motivated by this, we develop the alarming and prediction system for infection diseases. Such system integrates the data collected by hospital, pharmacies, and other infectious disease control monitoring system as well as Internet public opinion. And then through data processing, mining analysis, monitoring public opinion, as we as the integration of BP artificial neural network modes, SIR model and the complex network model, the system provides early Alarming and Prediction and forecasting functions of infectious diseases.
KeywordsPublic opinion mining BP artificial neural model SIR model Complex network model
This paper was partially supported by National Sci-Tech Support Plan 2015BAH10F01 and NSFC grant U1509216, 61472099, 61133002 and the Scientific Research Foundation for the Returned Overseas Chinese Scholars of Heilongjiang Province LC2016026.
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