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《Geomatics World》 2016-06
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Comparing of Spatio-Temporal Diffusion Prediction Models of Dengue Fevers Based on Machine Learning

CHEN Yebin;LI Weihong;HUA Jiamin;LIANG Xuemei;School of Geography, South China Normal University;School of Geographical Sciences, Xinjiang University;  
BP neural network, GA-BP neural network and SVR model are commonly used in the field of machine learning, but few of them are involved in the diffusion prediction of dengue fever. In this paper, we took Dengue Fever in the downtown of Guangzhou city as an example, compared the spatio-temporal dynamics prediction results of BP neural network, GA-BP neural network and SVR models. The results showed that, the prediction effect of SVR model was superior to BP and GA-BP model; the performance of GA-BP model was better than BP and SVR model; SVR and GABP model were feasible in the prediction of Dengue Fever.
【Fund】: 国家自然科学基金项目(41171141)资助
【CateGory Index】: R512.8;TP181
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