These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
128 related articles for article (PubMed ID: 36045185)
1. The development of dissolved oxygen forecast model using hybrid machine learning algorithm with hydro-meteorological variables. Ahmed AAM; Jui SJJ; Chowdhury MAI; Ahmed O; Sutradha A Environ Sci Pollut Res Int; 2023 Jan; 30(3):7851-7873. PubMed ID: 36045185 [TBL] [Abstract][Full Text] [Related]
2. Prediction of 5-day biochemical oxygen demand in the Buriganga River of Bangladesh using novel hybrid machine learning algorithms. Nafsin N; Li J Water Environ Res; 2022 May; 94(5):e10718. PubMed ID: 35502725 [TBL] [Abstract][Full Text] [Related]
3. Analysis of dissolved oxygen influencing factors and concentration prediction using input variable selection technique: A hybrid machine learning approach. Liu W; Lin S; Li X; Li W; Deng H; Fang H; Li W J Environ Manage; 2024 Apr; 357():120777. PubMed ID: 38581893 [TBL] [Abstract][Full Text] [Related]
4. Robust clustering-based hybrid technique enabling reliable reservoir water quality prediction with uncertainty quantification and spatial analysis. Fooladi M; Nikoo MR; Mirghafari R; Madramootoo CA; Al-Rawas G; Nazari R J Environ Manage; 2024 Jun; 362():121259. PubMed ID: 38830281 [TBL] [Abstract][Full Text] [Related]
5. Comparison of the performance of decision tree (DT) algorithms and extreme learning machine (ELM) model in the prediction of water quality of the Upper Green River watershed. Anmala J; Turuganti V Water Environ Res; 2021 Nov; 93(11):2360-2373. PubMed ID: 34528328 [TBL] [Abstract][Full Text] [Related]
6. Hybrid WT-CNN-GRU-based model for the estimation of reservoir water quality variables considering spatio-temporal features. Zamani MG; Nikoo MR; Al-Rawas G; Nazari R; Rastad D; Gandomi AH J Environ Manage; 2024 May; 358():120756. PubMed ID: 38599080 [TBL] [Abstract][Full Text] [Related]
7. A water quality prediction model based on variational mode decomposition and the least squares support vector machine optimized by the sparrow search algorithm (VMD-SSA-LSSVM) of the Yangtze River, China. Song C; Yao L; Hua C; Ni Q Environ Monit Assess; 2021 May; 193(6):363. PubMed ID: 34041601 [TBL] [Abstract][Full Text] [Related]
8. Hybrid decision tree-based machine learning models for short-term water quality prediction. Lu H; Ma X Chemosphere; 2020 Jun; 249():126169. PubMed ID: 32078849 [TBL] [Abstract][Full Text] [Related]
9. Surface water quality index forecasting using multivariate complementing approach reinforced with locally weighted linear regression model. Hai T; Ahmadianfar I; Halder B; Heddam S; Al-Areeq AM; Demir V; Kilinc HC; Abba SI; Tan ML; Homod RZ; Yaseen ZM Environ Sci Pollut Res Int; 2024 May; 31(22):32382-32406. PubMed ID: 38653893 [TBL] [Abstract][Full Text] [Related]
10. Biochemical oxygen demand prediction: development of hybrid wavelet-random forest and M5 model tree approach using feature selection algorithms. Golabi MR; Farzi S; Khodabakhshi F; Sohrabi Geshnigani F; Nazdane F; Radmanesh F Environ Sci Pollut Res Int; 2020 Sep; 27(27):34322-34336. PubMed ID: 32548747 [TBL] [Abstract][Full Text] [Related]
11. Estimating the incubated river water quality indicator based on machine learning and deep learning paradigms: BOD5 Prediction. Kim S; Alizamir M; Seo Y; Heddam S; Chung IM; Kim YO; Kisi O; Singh VP Math Biosci Eng; 2022 Sep; 19(12):12744-12773. PubMed ID: 36654020 [TBL] [Abstract][Full Text] [Related]
12. A stacked machine learning model for multi-step ahead prediction of lake surface water temperature. Di Nunno F; Zhu S; Ptak M; Sojka M; Granata F Sci Total Environ; 2023 Sep; 890():164323. PubMed ID: 37216992 [TBL] [Abstract][Full Text] [Related]
13. Predicting river dissolved oxygen time series based on stand-alone models and hybrid wavelet-based models. Xu C; Chen X; Zhang L J Environ Manage; 2021 Oct; 295():113085. PubMed ID: 34147993 [TBL] [Abstract][Full Text] [Related]
14. Prediction of the five-day biochemical oxygen demand and chemical oxygen demand in natural streams using machine learning methods. Najafzadeh M; Ghaemi A Environ Monit Assess; 2019 May; 191(6):380. PubMed ID: 31104155 [TBL] [Abstract][Full Text] [Related]
15. Robust machine learning algorithms for predicting coastal water quality index. Uddin MG; Nash S; Mahammad Diganta MT; Rahman A; Olbert AI J Environ Manage; 2022 Nov; 321():115923. PubMed ID: 35988401 [TBL] [Abstract][Full Text] [Related]
16. Application of machine learning in river water quality management: a review. Cojbasic S; Dmitrasinovic S; Kostic M; Turk Sekulic M; Radonic J; Dodig A; Stojkovic M Water Sci Technol; 2023 Nov; 88(9):2297-2308. PubMed ID: 37966184 [TBL] [Abstract][Full Text] [Related]
17. Prediction of meteorological drought and standardized precipitation index based on the random forest (RF), random tree (RT), and Gaussian process regression (GPR) models. Elbeltagi A; Pande CB; Kumar M; Tolche AD; Singh SK; Kumar A; Vishwakarma DK Environ Sci Pollut Res Int; 2023 Mar; 30(15):43183-43202. PubMed ID: 36648725 [TBL] [Abstract][Full Text] [Related]
18. Groundwater quality modeling and determining critical points: a comparison of machine learning to Best-Worst Method. Nasiri Khiavi A; Mostafazadeh R; Adhami M Environ Sci Pollut Res Int; 2023 Nov; 30(54):115758-115775. PubMed ID: 37889408 [TBL] [Abstract][Full Text] [Related]
19. AI-HydSu: An advanced hybrid approach using support vector regression and particle swarm optimization for dissolved oxygen forecasting. Li D; Wang X; Sun J; Yang H Math Biosci Eng; 2021 Apr; 18(4):3646-3666. PubMed ID: 34198404 [TBL] [Abstract][Full Text] [Related]
20. Estimation of daily dissolved oxygen concentration for river water quality using conventional regression analysis, multivariate adaptive regression splines, and TreeNet techniques. Nacar S; Mete B; Bayram A Environ Monit Assess; 2020 Nov; 192(12):752. PubMed ID: 33159587 [TBL] [Abstract][Full Text] [Related] [Next] [New Search]