456 related articles for article (PubMed ID: 35988401)
1. 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]
2. 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]
3. Predictive modeling of blood pressure during hemodialysis: a comparison of linear model, random forest, support vector regression, XGBoost, LASSO regression and ensemble method.
Huang JC; Tsai YC; Wu PY; Lien YH; Chien CY; Kuo CF; Hung JF; Chen SC; Kuo CH
Comput Methods Programs Biomed; 2020 Oct; 195():105536. PubMed ID: 32485511
[TBL] [Abstract][Full Text] [Related]
4. Data-driven modelling for assessing trophic status in marine ecosystems using machine learning approaches.
Uddin MG; Nash S; Rahman A; Dabrowski T; Olbert AI
Environ Res; 2024 Feb; 242():117755. PubMed ID: 38008200
[TBL] [Abstract][Full Text] [Related]
5. Machine learning prediction of tree species diversity using forest structure and environmental factors: a case study from the Hyrcanian forest, Iran.
Valizadeh E; Asadi H; Jaafari A; Tafazoli M
Environ Monit Assess; 2023 Oct; 195(11):1334. PubMed ID: 37851130
[TBL] [Abstract][Full Text] [Related]
6. 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]
7. A novel approach for estimating and predicting uncertainty in water quality index model using machine learning approaches.
Uddin MG; Nash S; Rahman A; Olbert AI
Water Res; 2023 Feb; 229():119422. PubMed ID: 36459893
[TBL] [Abstract][Full Text] [Related]
8. Prediction of weighted arithmetic water quality index for urban water quality using ensemble machine learning model.
Mohseni U; Pande CB; Chandra Pal S; Alshehri F
Chemosphere; 2024 Mar; 352():141393. PubMed ID: 38325619
[TBL] [Abstract][Full Text] [Related]
9. Using machine learning models to predict the effects of seasonal fluxes on Plesiomonas shigelloides population density.
Ekundayo TC; Ijabadeniyi OA; Igbinosa EO; Okoh AI
Environ Pollut; 2023 Jan; 317():120734. PubMed ID: 36455774
[TBL] [Abstract][Full Text] [Related]
10. A comprehensive review of water quality indices for lotic and lentic ecosystems.
Mogane LK; Masebe T; Msagati TAM; Ncube E
Environ Monit Assess; 2023 Jul; 195(8):926. PubMed ID: 37420028
[TBL] [Abstract][Full Text] [Related]
11. Performance Analysis of Conventional Machine Learning Algorithms for Identification of Chronic Kidney Disease in Type 1 Diabetes Mellitus Patients.
Chowdhury NH; Reaz MBI; Haque F; Ahmad S; Ali SHM; A Bakar AA; Bhuiyan MAS
Diagnostics (Basel); 2021 Dec; 11(12):. PubMed ID: 34943504
[TBL] [Abstract][Full Text] [Related]
12. A comprehensive method for improvement of water quality index (WQI) models for coastal water quality assessment.
Uddin MG; Nash S; Rahman A; Olbert AI
Water Res; 2022 Jul; 219():118532. PubMed ID: 35533623
[TBL] [Abstract][Full Text] [Related]
13. Development and validation of explainable machine-learning models for carotid atherosclerosis early screening.
Yun K; He T; Zhen S; Quan M; Yang X; Man D; Zhang S; Wang W; Han X
J Transl Med; 2023 May; 21(1):353. PubMed ID: 37246225
[TBL] [Abstract][Full Text] [Related]
14. Artificial intelligence based system for predicting permanent stoma after sphincter saving operations.
Kuo CY; Kuo LJ; Lin YK
Sci Rep; 2023 Sep; 13(1):16039. PubMed ID: 37749194
[TBL] [Abstract][Full Text] [Related]
15. Improved soil carbon stock spatial prediction in a Mediterranean soil erosion site through robust machine learning techniques.
Mosaid H; Barakat A; John K; Faouzi E; Bustillo V; El Garnaoui M; Heung B
Environ Monit Assess; 2024 Jan; 196(2):130. PubMed ID: 38198014
[TBL] [Abstract][Full Text] [Related]
16. Prediction of Compressive Strength of Fly Ash Based Concrete Using Individual and Ensemble Algorithm.
Ahmad A; Farooq F; Niewiadomski P; Ostrowski K; Akbar A; Aslam F; Alyousef R
Materials (Basel); 2021 Feb; 14(4):. PubMed ID: 33567526
[TBL] [Abstract][Full Text] [Related]
17. 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]
18. Mapping of groundwater productivity potential with machine learning algorithms: A case study in the provincial capital of Baluchistan, Pakistan.
Rasool U; Yin X; Xu Z; Rasool MA; Senapathi V; Hussain M; Siddique J; Trabucco JC
Chemosphere; 2022 Sep; 303(Pt 3):135265. PubMed ID: 35691394
[TBL] [Abstract][Full Text] [Related]
19. Optimisation and interpretation of machine and deep learning models for improved water quality management in Lake Loktak.
Talukdar S; Shahfahad ; Bera S; Naikoo MW; Ramana GV; Mallik S; Kumar PA; Rahman A
J Environ Manage; 2024 Feb; 351():119866. PubMed ID: 38147770
[TBL] [Abstract][Full Text] [Related]
20. Evaluation of machine learning models for predicting TiO
Javed MF; Shahab MZ; Asif U; Najeh T; Aslam F; Ali M; Khan I
Sci Rep; 2024 Jun; 14(1):13688. PubMed ID: 38871797
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
