191 related articles for article (PubMed ID: 38102558)
1. A hybrid model for hand-foot-mouth disease prediction based on ARIMA-EEMD-LSTM.
Wan Y; Song P; Liu J; Xu X; Lei X
BMC Infect Dis; 2023 Dec; 23(1):879. PubMed ID: 38102558
[TBL] [Abstract][Full Text] [Related]
2. Comparison of ARIMA and LSTM in Forecasting the Incidence of HFMD Combined and Uncombined with Exogenous Meteorological Variables in Ningbo, China.
Zhang R; Guo Z; Meng Y; Wang S; Li S; Niu R; Wang Y; Guo Q; Li Y
Int J Environ Res Public Health; 2021 Jun; 18(11):. PubMed ID: 34200378
[TBL] [Abstract][Full Text] [Related]
3. A Novel Hybrid Data-Driven Model for Daily Land Surface Temperature Forecasting Using Long Short-Term Memory Neural Network Based on Ensemble Empirical Mode Decomposition.
Zhang X; Zhang Q; Zhang G; Nie Z; Gui Z; Que H
Int J Environ Res Public Health; 2018 May; 15(5):. PubMed ID: 29883381
[TBL] [Abstract][Full Text] [Related]
4. Forecasting incidence of hand, foot and mouth disease using BP neural networks in Jiangsu province, China.
Liu W; Bao C; Zhou Y; Ji H; Wu Y; Shi Y; Shen W; Bao J; Li J; Hu J; Huo X
BMC Infect Dis; 2019 Oct; 19(1):828. PubMed ID: 31590636
[TBL] [Abstract][Full Text] [Related]
5. A Hybrid Model for Coronavirus Disease 2019 Forecasting Based on Ensemble Empirical Mode Decomposition and Deep Learning.
Liu S; Wan Y; Yang W; Tan A; Jian J; Lei X
Int J Environ Res Public Health; 2022 Dec; 20(1):. PubMed ID: 36612939
[TBL] [Abstract][Full Text] [Related]
6. Epidemiological characteristics, spatial clusters and monthly incidence prediction of hand, foot and mouth disease from 2017 to 2022 in Shanxi Province, China.
Ma Y; Xu S; Dong A; An J; Qin Y; Yang H; Yu H
Epidemiol Infect; 2023 Mar; 151():e54. PubMed ID: 37039461
[TBL] [Abstract][Full Text] [Related]
7. Predicting the incidence of hand, foot and mouth disease in Sichuan province, China using the ARIMA model.
Liu L; Luan RS; Yin F; Zhu XP; Lü Q
Epidemiol Infect; 2016 Jan; 144(1):144-51. PubMed ID: 26027606
[TBL] [Abstract][Full Text] [Related]
8. Development and evaluation of a deep learning approach for modeling seasonality and trends in hand-foot-mouth disease incidence in mainland China.
Wang Y; Xu C; Zhang S; Yang L; Wang Z; Zhu Y; Yuan J
Sci Rep; 2019 May; 9(1):8046. PubMed ID: 31142826
[TBL] [Abstract][Full Text] [Related]
9. Application of seasonal auto-regressive integrated moving average model in forecasting the incidence of hand-foot-mouth disease in Wuhan, China.
Peng Y; Yu B; Wang P; Kong DG; Chen BH; Yang XB
J Huazhong Univ Sci Technolog Med Sci; 2017 Dec; 37(6):842-848. PubMed ID: 29270741
[TBL] [Abstract][Full Text] [Related]
10. Comparison of autoregressive integrated moving average model and generalised regression neural network model for prediction of haemorrhagic fever with renal syndrome in China: a time-series study.
Wang YW; Shen ZZ; Jiang Y
BMJ Open; 2019 Jun; 9(6):e025773. PubMed ID: 31209084
[TBL] [Abstract][Full Text] [Related]
11. Study of the influence of meteorological factors on HFMD and prediction based on the LSTM algorithm in Fuzhou, China.
Zhu H; Chen S; Liang R; Feng Y; Joldosh A; Xie Z; Chen G; Li L; Chen K; Fang Y; Ou J
BMC Infect Dis; 2023 May; 23(1):299. PubMed ID: 37147566
[TBL] [Abstract][Full Text] [Related]
12. Monthly precipitation prediction in Luoyang city based on EEMD-LSTM-ARIMA model.
Zhao J; Nie G; Wen Y
Water Sci Technol; 2023 Jan; 87(1):318-335. PubMed ID: 36640040
[TBL] [Abstract][Full Text] [Related]
13. Study on the National Monthly Reported Severe Cases of Hand-foot-mouth Disease Forecasted by Autoregressive Integrated Moving Average Model.
Zhang S; Qiu Q; Wang Y
Bing Du Xue Bao; 2017 Jan; 33(1):77-81. PubMed ID: 30702825
[TBL] [Abstract][Full Text] [Related]
14. Comparison of ARIMA and LSTM for prediction of hemorrhagic fever at different time scales in China.
Zhang R; Song H; Chen Q; Wang Y; Wang S; Li Y
PLoS One; 2022; 17(1):e0262009. PubMed ID: 35030203
[TBL] [Abstract][Full Text] [Related]
15. A hybrid model for tuberculosis forecasting based on empirical mode decomposition in China.
Zhao R; Liu J; Zhao Z; Zhai M; Ren H; Wang X; Li Y; Cui Y; Qiao Y; Ren J; Chen L; Qiu L
BMC Infect Dis; 2023 Oct; 23(1):665. PubMed ID: 37805543
[TBL] [Abstract][Full Text] [Related]
16. Prediction of hepatitis E using machine learning models.
Guo Y; Feng Y; Qu F; Zhang L; Yan B; Lv J
PLoS One; 2020; 15(9):e0237750. PubMed ID: 32941452
[TBL] [Abstract][Full Text] [Related]
17. Enhancing drought prediction precision with EEMD-ARIMA modeling based on standardized precipitation index.
Rezaiy R; Shabri A
Water Sci Technol; 2024 Feb; 89(3):745-770. PubMed ID: 38358500
[TBL] [Abstract][Full Text] [Related]
18. Predicting the hand, foot, and mouth disease incidence using search engine query data and climate variables: an ecological study in Guangdong, China.
Du Z; Xu L; Zhang W; Zhang D; Yu S; Hao Y
BMJ Open; 2017 Oct; 7(10):e016263. PubMed ID: 28988169
[TBL] [Abstract][Full Text] [Related]
19. The research of ARIMA, GM(1,1), and LSTM models for prediction of TB cases in China.
Zhao D; Zhang H; Cao Q; Wang Z; He S; Zhou M; Zhang R
PLoS One; 2022; 17(2):e0262734. PubMed ID: 35196309
[TBL] [Abstract][Full Text] [Related]
20. Research on hand, foot and mouth disease incidence forecasting using hybrid model in mainland China.
Zhao D; Zhang H; Zhang R; He S
BMC Public Health; 2023 Mar; 23(1):619. PubMed ID: 37003988
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
