258 related articles for article (PubMed ID: 31783697)
1. Predicting Seasonal Influenza Based on SARIMA Model, in Mainland China from 2005 to 2018.
Cong J; Ren M; Xie S; Wang P
Int J Environ Res Public Health; 2019 Nov; 16(23):. PubMed ID: 31783697
[TBL] [Abstract][Full Text] [Related]
2. A new hybrid model SARIMA-ETS-SVR for seasonal influenza incidence prediction in mainland China.
Zhao D; Zhang R
J Infect Dev Ctries; 2023 Nov; 17(11):1581-1590. PubMed ID: 38064398
[TBL] [Abstract][Full Text] [Related]
3. Forecasting seasonal influenza activity in Canada-Comparing seasonal Auto-Regressive integrated moving average and artificial neural network approaches for public health preparedness.
Orang A; Berke O; Poljak Z; Greer AL; Rees EE; Ng V
Zoonoses Public Health; 2024 May; 71(3):304-313. PubMed ID: 38331569
[TBL] [Abstract][Full Text] [Related]
4. Time-series modelling and forecasting of hand, foot and mouth disease cases in China from 2008 to 2018.
Tian CW; Wang H; Luo XM
Epidemiol Infect; 2019 Jan; 147():e82. PubMed ID: 30868999
[TBL] [Abstract][Full Text] [Related]
5. Study on the prediction effect of a combined model of SARIMA and LSTM based on SSA for influenza in Shanxi Province, China.
Zhao Z; Zhai M; Li G; Gao X; Song W; Wang X; Ren H; Cui Y; Qiao Y; Ren J; Chen L; Qiu L
BMC Infect Dis; 2023 Feb; 23(1):71. PubMed ID: 36747126
[TBL] [Abstract][Full Text] [Related]
6. Temporal trends analysis of tuberculosis morbidity in mainland China from 1997 to 2025 using a new SARIMA-NARNNX hybrid model.
Wang Y; Xu C; Zhang S; Wang Z; Yang L; Zhu Y; Yuan J
BMJ Open; 2019 Jul; 9(7):e024409. PubMed ID: 31371283
[TBL] [Abstract][Full Text] [Related]
7. Epidemiological features and time-series analysis of influenza incidence in urban and rural areas of Shenyang, China, 2010-2018.
Chen Y; Leng K; Lu Y; Wen L; Qi Y; Gao W; Chen H; Bai L; An X; Sun B; Wang P; Dong J
Epidemiol Infect; 2020 Feb; 148():e29. PubMed ID: 32054544
[TBL] [Abstract][Full Text] [Related]
8. Application of a combined model with seasonal autoregressive integrated moving average and support vector regression in forecasting hand-foot-mouth disease incidence in Wuhan, China.
Zou JJ; Jiang GF; Xie XX; Huang J; Yang XB
Medicine (Baltimore); 2019 Feb; 98(6):e14195. PubMed ID: 30732135
[TBL] [Abstract][Full Text] [Related]
9. Forecasting mortality of road traffic injuries in China using seasonal autoregressive integrated moving average model.
Zhang X; Pang Y; Cui M; Stallones L; Xiang H
Ann Epidemiol; 2015 Feb; 25(2):101-6. PubMed ID: 25467006
[TBL] [Abstract][Full Text] [Related]
10. Forecasting the incidence of tuberculosis in China using the seasonal auto-regressive integrated moving average (SARIMA) model.
Mao Q; Zhang K; Yan W; Cheng C
J Infect Public Health; 2018; 11(5):707-712. PubMed ID: 29730253
[TBL] [Abstract][Full Text] [Related]
11. Forecast of the trend in incidence of acute hemorrhagic conjunctivitis in China from 2011-2019 using the Seasonal Autoregressive Integrated Moving Average (SARIMA) and Exponential Smoothing (ETS) models.
Liu H; Li C; Shao Y; Zhang X; Zhai Z; Wang X; Qi X; Wang J; Hao Y; Wu Q; Jiao M
J Infect Public Health; 2020 Feb; 13(2):287-294. PubMed ID: 31953020
[TBL] [Abstract][Full Text] [Related]
12. Forecasting the monthly incidence of scarlet fever in Chongqing, China using the SARIMA model.
Wu WW; Li Q; Tian DC; Zhao H; Xia Y; Xiong Y; Su K; Tang WG; Chen X; Wang J; Qi L
Epidemiol Infect; 2022 Apr; 150():e90. PubMed ID: 35543101
[TBL] [Abstract][Full Text] [Related]
13. Time series analysis of rubella incidence in Chongqing, China using SARIMA and BPNN mathematical models.
Chen Q; Zhao H; Qiu H; Wang Q; Zeng D; Ye M
J Infect Dev Ctries; 2022 Aug; 16(8):1343-1350. PubMed ID: 36099379
[TBL] [Abstract][Full Text] [Related]
14. SARFIMA model prediction for infectious diseases: application to hemorrhagic fever with renal syndrome and comparing with SARIMA.
Qi C; Zhang D; Zhu Y; Liu L; Li C; Wang Z; Li X
BMC Med Res Methodol; 2020 Sep; 20(1):243. PubMed ID: 32993517
[TBL] [Abstract][Full Text] [Related]
15. Seasonality and Trend Forecasting of Tuberculosis Incidence in Chongqing, China.
Liao Z; Zhang X; Zhang Y; Peng D
Interdiscip Sci; 2019 Mar; 11(1):77-85. PubMed ID: 30734907
[TBL] [Abstract][Full Text] [Related]
16. Seasonal behavior and forecasting trends of tuberculosis incidence in Holy Kerbala, Iraq.
Mohammed SH; Ahmed MM; Al-Mousawi AM; Azeez A
Int J Mycobacteriol; 2018; 7(4):361-367. PubMed ID: 30531036
[TBL] [Abstract][Full Text] [Related]
17. Time series analysis of influenza incidence in Chinese provinces from 2004 to 2011.
Song X; Xiao J; Deng J; Kang Q; Zhang Y; Xu J
Medicine (Baltimore); 2016 Jun; 95(26):e3929. PubMed ID: 27367989
[TBL] [Abstract][Full Text] [Related]
18. Time Series Models for Short Term Prediction of the Incidence of Japanese Encephalitis in Xianyang City, P R China
Zhang RQ; Li FY; Liu JL; Liu MN; Luo WR; Ma T; Ma B; Zhang ZG
Chin Med Sci J; 2017 Sep; 32(3):152-160. PubMed ID: 28956742
[TBL] [Abstract][Full Text] [Related]
19. Time series analysis and forecasting of chlamydia trachomatis incidence using surveillance data from 2008 to 2019 in Shenzhen, China.
Weng RX; Fu HL; Zhang CL; Ye JB; Hong FC; Chen XS; Cai YM
Epidemiol Infect; 2020 Mar; 148():e76. PubMed ID: 32178748
[TBL] [Abstract][Full Text] [Related]
20. A Combined Model of SARIMA and Prophet Models in Forecasting AIDS Incidence in Henan Province, China.
Luo Z; Jia X; Bao J; Song Z; Zhu H; Liu M; Yang Y; Shi X
Int J Environ Res Public Health; 2022 May; 19(10):. PubMed ID: 35627447
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]