Algorithm for performing flood-caused diarrhea outbreak risk remote sensing diagnosis by utilizing remote sensing data and expert knowledge base
An expert knowledge base and remote sensing data technology, applied in the field of remote sensing diagnosis of diarrhea outbreak risk caused by floods, can solve problems such as time-consuming, difficult to expand to large-scale areas, and inability to obtain relevant data, so as to reduce workload and reduce medical security Costs, morbidity and mortality reduction effects
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[0015] figure 1 It is a flow chart of constructing the remote sensing diagnosis algorithm model of flood-induced diarrhea outbreak risk. As can be seen from the figure, building a cholera prediction model includes the following three steps:
[0016] 1) Use satellite remote sensing data (SAR and airborne high-resolution optical remote sensing data) to obtain flood outbreak area and flood outbreak duration data information; use inverse distance weighting difference based on population density data, dissolved oxygen data and other water quality survey data The algorithm (IDW) analyzes and solves the spatial distribution characteristics of these data;
[0017] 2) Construct a model formula based on the relationship between the flood information obtained from the above remote sensing data and the environmental elements and the diarrhea incidence data;
[0018] 3) The expert system is used to fit the model based on the historical data of the risk of diarrheal disease outbreaks caus...
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