130 related articles for article (PubMed ID: 34894494)
1. A study of uncertainties in groundwater vulnerability modelling using Bayesian model averaging (BMA).
Gharekhani M; Nadiri AA; Khatibi R; Sadeghfam S; Asghari Moghaddam A
J Environ Manage; 2022 Feb; 303():114168. PubMed ID: 34894494
[TBL] [Abstract][Full Text] [Related]
2. Vulnerability Indexing to Saltwater Intrusion from Models at Two Levels using Artificial Intelligence Multiple Model (AIMM).
Moazamnia M; Hassanzadeh Y; Nadiri AA; Sadeghfam S
J Environ Manage; 2020 Feb; 255():109871. PubMed ID: 32063320
[TBL] [Abstract][Full Text] [Related]
3. Formulating Convolutional Neural Network for mapping total aquifer vulnerability to pollution.
Nadiri AA; Moazamnia M; Sadeghfam S; Gnanachandrasamy G; Venkatramanan S
Environ Pollut; 2022 Jul; 304():119208. PubMed ID: 35351597
[TBL] [Abstract][Full Text] [Related]
4. Uncertainty-based saltwater intrusion prediction using integrated Bayesian machine learning modeling (IBMLM) in a deep aquifer.
Yin J; Huang Y; Lu C; Liu Z
J Environ Manage; 2024 Mar; 354():120252. PubMed ID: 38394869
[TBL] [Abstract][Full Text] [Related]
5. Mapping specific vulnerability of multiple confined and unconfined aquifers by using artificial intelligence to learn from multiple DRASTIC frameworks.
Nadiri AA; Sedghi Z; Khatibi R; Sadeghfam S
J Environ Manage; 2018 Dec; 227():415-428. PubMed ID: 30218838
[TBL] [Abstract][Full Text] [Related]
6. Groundwater vulnerability indices conditioned by Supervised Intelligence Committee Machine (SICM).
Nadiri AA; Gharekhani M; Khatibi R; Sadeghfam S; Moghaddam AA
Sci Total Environ; 2017 Jan; 574():691-706. PubMed ID: 27664756
[TBL] [Abstract][Full Text] [Related]
7. Quantifying the groundwater total contamination risk using an inclusive multi-level modelling strategy.
Gharekhani M; Nadiri AA; Khatibi R; Nikoo MR; Barzegar R; Sadeghfam S; Moghaddam AA
J Environ Manage; 2023 Apr; 332():117287. PubMed ID: 36716540
[TBL] [Abstract][Full Text] [Related]
8. An investigation into time-variant subsidence potentials using inclusive multiple modelling strategies.
Gharekhani M; Nadiri AA; Khatibi R; Sadeghfam S
J Environ Manage; 2021 Sep; 294():112949. PubMed ID: 34130140
[TBL] [Abstract][Full Text] [Related]
9. A hierarchical Bayesian model averaging framework for groundwater prediction under uncertainty.
Chitsazan N; Tsai FT
Ground Water; 2015; 53(2):305-16. PubMed ID: 24890644
[TBL] [Abstract][Full Text] [Related]
10. Bayesian Chance-Constrained Hydraulic Barrier Design under Geological Structure Uncertainty.
Chitsazan N; Pham HV; Tsai FT
Ground Water; 2015; 53(6):908-19. PubMed ID: 25510348
[TBL] [Abstract][Full Text] [Related]
11. Groundwater salinization risk assessment using combined artificial intelligence models.
Dhaoui O; Antunes IM; Benhenda I; Agoubi B; Kharroubi A
Environ Sci Pollut Res Int; 2024 May; 31(23):33398-33413. PubMed ID: 38678534
[TBL] [Abstract][Full Text] [Related]
12. Assessment of groundwater vulnerability using genetic algorithm and random forest methods (case study: Miandoab plain, NW of Iran).
Norouzi H; Moghaddam AA; Celico F; Shiri J
Environ Sci Pollut Res Int; 2021 Aug; 28(29):39598-39613. PubMed ID: 33761080
[TBL] [Abstract][Full Text] [Related]
13. Modeling of aquifer vulnerability index using deep learning neural networks coupling with optimization algorithms.
Elzain HE; Chung SY; Senapathi V; Sekar S; Park N; Mahmoud AA
Environ Sci Pollut Res Int; 2021 Oct; 28(40):57030-57045. PubMed ID: 34081280
[TBL] [Abstract][Full Text] [Related]
14. Comparative Analysis of Artificial Intelligence Models for Accurate Estimation of Groundwater Nitrate Concentration.
Band SS; Janizadeh S; Pal SC; Chowdhuri I; Siabi Z; Norouzi A; Melesse AM; Shokri M; Mosavi A
Sensors (Basel); 2020 Oct; 20(20):. PubMed ID: 33053663
[TBL] [Abstract][Full Text] [Related]
15. Estimating evapotranspiration by coupling Bayesian model averaging methods with machine learning algorithms.
Yang Y; Sun H; Xue J; Liu Y; Liu L; Yan D; Gui D
Environ Monit Assess; 2021 Mar; 193(3):156. PubMed ID: 33655353
[TBL] [Abstract][Full Text] [Related]
16. Multi-model ensemble simulated non-point source pollution based on Bayesian model averaging method and model uncertainty analysis.
Wang H; Lu K; Zhao Y; Zhang J; Hua J; Lin X
Environ Sci Pollut Res Int; 2020 Dec; 27(35):44482-44493. PubMed ID: 32772284
[TBL] [Abstract][Full Text] [Related]
17. Stochastic nitrate simulation under hydraulic conductivity uncertainty of an agricultural basin aquifer at Eastern Thessaly, Greece.
Sidiropoulos P; Mylopoulos N; Vasiliades L; Loukas A
Environ Sci Pollut Res Int; 2021 Dec; 28(46):65700-65715. PubMed ID: 34319525
[TBL] [Abstract][Full Text] [Related]
18. Optimization of DRASTIC method by artificial neural network, nitrate vulnerability index, and composite DRASTIC models to assess groundwater vulnerability for unconfined aquifer of Shiraz Plain, Iran.
Baghapour MA; Fadaei Nobandegani A; Talebbeydokhti N; Bagherzadeh S; Nadiri AA; Gharekhani M; Chitsazan N
J Environ Health Sci Eng; 2016; 14():13. PubMed ID: 27508082
[TBL] [Abstract][Full Text] [Related]
19. Bayesian model averaging in time-series studies of air pollution and mortality.
Thomas DC; Jerrett M; Kuenzli N; Louis TA; Dominici F; Zeger S; Schwarz J; Burnett RT; Krewski D; Bates D
J Toxicol Environ Health A; 2007 Feb; 70(3-4):311-5. PubMed ID: 17365593
[TBL] [Abstract][Full Text] [Related]
20. Bayesian model averaging of Bayesian network classifiers over multiple node-orders: application to sparse datasets.
Hwang KB; Zhang BT
IEEE Trans Syst Man Cybern B Cybern; 2005 Dec; 35(6):1302-10. PubMed ID: 16366254
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]