534 related articles for article (PubMed ID: 35696432)
21. Seasonal patterns of dengue fever and associated climate factors in 4 provinces in Vietnam from 1994 to 2013.
Lee HS; Nguyen-Viet H; Nam VS; Lee M; Won S; Duc PP; Grace D
BMC Infect Dis; 2017 Mar; 17(1):218. PubMed ID: 28320341
[TBL] [Abstract][Full Text] [Related]
22. Use of one-dimensional CNN for input data size reduction in LSTM for improved computational efficiency and accuracy in hourly rainfall-runoff modeling.
Ishida K; Ercan A; Nagasato T; Kiyama M; Amagasaki M
J Environ Manage; 2024 May; 359():120931. PubMed ID: 38678895
[TBL] [Abstract][Full Text] [Related]
23. Artificial Intelligence Approach for Severe Dengue Early Warning System.
Anggraini Ningrum DN; Li YJ; Hsu CY; Solihuddin Muhtar M; Pandu Suhito H
Stud Health Technol Inform; 2024 Jan; 310():881-885. PubMed ID: 38269935
[TBL] [Abstract][Full Text] [Related]
24. 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]
25. Weather integrated multiple machine learning models for prediction of dengue prevalence in India.
Kakarla SG; Kondeti PK; Vavilala HP; Boddeda GSB; Mopuri R; Kumaraswamy S; Kadiri MR; Mutheneni SR
Int J Biometeorol; 2023 Feb; 67(2):285-297. PubMed ID: 36380258
[TBL] [Abstract][Full Text] [Related]
26. Road Traffic Forecast Based on Meteorological Information through Deep Learning Methods.
Braz FJ; Ferreira J; Gonçalves F; Weege K; Almeida J; Baldo F; Gonçalves P
Sensors (Basel); 2022 Jun; 22(12):. PubMed ID: 35746265
[TBL] [Abstract][Full Text] [Related]
27. Performance evaluation of Emergency Department patient arrivals forecasting models by including meteorological and calendar information: A comparative study.
Sudarshan VK; Brabrand M; Range TM; Wiil UK
Comput Biol Med; 2021 Aug; 135():104541. PubMed ID: 34166880
[TBL] [Abstract][Full Text] [Related]
28. Large-scale multivariate forecasting models for Dengue - LSTM versus random forest regression.
Mussumeci E; Codeço Coelho F
Spat Spatiotemporal Epidemiol; 2020 Nov; 35():100372. PubMed ID: 33138951
[TBL] [Abstract][Full Text] [Related]
29. Spatiotemporal analysis of historical records (2001-2012) on dengue fever in Vietnam and development of a statistical model for forecasting risk.
Bett B; Grace D; Lee HS; Lindahl J; Nguyen-Viet H; Phuc PD; Quyen NH; Tu TA; Phu TD; Tan DQ; Nam VS
PLoS One; 2019; 14(11):e0224353. PubMed ID: 31774823
[TBL] [Abstract][Full Text] [Related]
30. Climatic-driven seasonality of emerging dengue fever in Hanoi, Vietnam.
Do TT; Martens P; Luu NH; Wright P; Choisy M
BMC Public Health; 2014 Oct; 14():1078. PubMed ID: 25323458
[TBL] [Abstract][Full Text] [Related]
31. IoT and Ensemble Long-Short-Term-Memory-Based Evapotranspiration Forecasting for Riyadh.
Nauman MA; Saeed M; Saidani O; Javed T; Almuqren L; Bashir RN; Jahangir R
Sensors (Basel); 2023 Sep; 23(17):. PubMed ID: 37688039
[TBL] [Abstract][Full Text] [Related]
32. A novel bidirectional LSTM deep learning approach for COVID-19 forecasting.
Aung NN; Pang J; Chua MCH; Tan HX
Sci Rep; 2023 Oct; 13(1):17953. PubMed ID: 37863921
[TBL] [Abstract][Full Text] [Related]
33. A Deep CNN-LSTM Model for Particulate Matter (PM
Huang CJ; Kuo PH
Sensors (Basel); 2018 Jul; 18(7):. PubMed ID: 29996546
[TBL] [Abstract][Full Text] [Related]
34. Uncertainty and sensitivity analysis of deep learning models for diurnal temperature range (DTR) forecasting over five Indian cities.
Sankalp S; Sahoo BB; Sahoo SN
Environ Monit Assess; 2023 Jan; 195(2):291. PubMed ID: 36633692
[TBL] [Abstract][Full Text] [Related]
35. An enhanced drought forecasting in coastal arid regions using deep learning approach with evaporation index.
Al Moteri M; Alrowais F; Mtouaa W; Aljehane NO; Alotaibi SS; Marzouk R; Mustafa Hilal A; Ahmed NA
Environ Res; 2024 Apr; 246():118171. PubMed ID: 38215925
[TBL] [Abstract][Full Text] [Related]
36. Deep-Learning Model for Influenza Prediction From Multisource Heterogeneous Data in a Megacity: Model Development and Evaluation.
Yang L; Li G; Yang J; Zhang T; Du J; Liu T; Zhang X; Han X; Li W; Ma L; Feng L; Yang W
J Med Internet Res; 2023 Feb; 25():e44238. PubMed ID: 36780207
[TBL] [Abstract][Full Text] [Related]
37. Deep learning time series prediction models in surveillance data of hepatitis incidence in China.
Xia Z; Qin L; Ning Z; Zhang X
PLoS One; 2022; 17(4):e0265660. PubMed ID: 35417459
[TBL] [Abstract][Full Text] [Related]
38. Climate Variability and Dengue Hemorrhagic Fever in Hanoi, Viet Nam, During 2008 to 2015.
Thi Tuyet-Hanh T; Nhat Cam N; Thi Thanh Huong L; Khanh Long T; Mai Kien T; Thi Kim Hanh D; Huu Quyen N; Nu Quy Linh T; Rocklöv J; Quam M; Van Minh H
Asia Pac J Public Health; 2018 Sep; 30(6):532-541. PubMed ID: 30045631
[TBL] [Abstract][Full Text] [Related]
39. An improved SPEI drought forecasting approach using the long short-term memory neural network.
Dikshit A; Pradhan B; Huete A
J Environ Manage; 2021 Apr; 283():111979. PubMed ID: 33482453
[TBL] [Abstract][Full Text] [Related]
40. A multivariate multi-step LSTM forecasting model for tuberculosis incidence with model explanation in Liaoning Province, China.
Yang E; Zhang H; Guo X; Zang Z; Liu Z; Liu Y
BMC Infect Dis; 2022 May; 22(1):490. PubMed ID: 35606725
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]