TDDF: HFMD Outpatients Prediction Based on Time Series Decomposition and Heterogenous Data Fusion in Xiamen, China

被引：10
|
作者：
Wang, Zhijin [1 ]
Huang, Yaohui [2 ]
He, Bingyan [1 ]
Luo, Ting [2 ]
Wang, Yongming [3 ]
Lin, Yingxian [1 ]
机构：
[1] Jimei Univ, Comp Engn Coll, Yinjiang Rd 185, Xiamen 361021, Peoples R China
[2] Jimei Univ, Chengyi Univ Coll, Jimei Rd 199, Xiamen 361021, Peoples R China
[3] China Elect Technol Grp Corp, Shandong Middle Rd 337, Shanghai 200001, Peoples R China
来源：
ADVANCED DATA MINING AND APPLICATIONS, ADMA 2019 | 2019年 / 11888卷
关键词：
HFMD prediction; Meteorological factor; Baidu search index;
D O I：
10.1007/978-3-030-35231-8_48
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Hand, foot and mouth disease (HFMD) is a common infectious disease in global public health. In this paper, the time series decomposition and heterogeneous data fusion (TDDF) method is proposed to enhance features in the performance of HFMD outpatients prediction. The TDDF first represents meteorological features and Baidu search index features with the consideration of lags, then those features are fused into decomposed historical HFMD cases to predict coming outpatient cases. Experimental results and analyses on the real collected records show the efficiency and effectiveness of TDDF on regression methods.
引用
收藏
页码：658 / 667
页数：10
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