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.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

277 related articles for article (PubMed ID: 34491495)

  • 1. Groundwater quality modeling using a novel hybrid data-intelligence model based on gray wolf optimization algorithm and multi-layer perceptron artificial neural network: a case study in Asadabad Plain, Hamedan, Iran.
    Ghobadi A; Cheraghi M; Sobhanardakani S; Lorestani B; Merrikhpour H
    Environ Sci Pollut Res Int; 2022 Feb; 29(6):8716-8730. PubMed ID: 34491495
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Comments on "Groundwater quality modeling using a novel hybrid data-intelligence model based on gray wolf optimization algorithm and multi-layer perceptron artificial neural network: a case study in Asadabad Plain, Hamedan, Iran" Cheraghi, Mehrdad et al. (10.1007/s11356-021-16300-4).
    Başakın EE
    Environ Sci Pollut Res Int; 2022 Jun; 29(27):41869-41871. PubMed ID: 35334047
    [No Abstract]   [Full Text] [Related]  

  • 3. Shannon entropy of performance metrics to choose the best novel hybrid algorithm to predict groundwater level (case study: Tabriz plain, Iran).
    Saroughi M; Mirzania E; Achite M; Katipoğlu OM; Ehteram M
    Environ Monit Assess; 2024 Feb; 196(3):227. PubMed ID: 38305997
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Artificial intelligence models versus empirical equations for modeling monthly reference evapotranspiration.
    Tikhamarine Y; Malik A; Souag-Gamane D; Kisi O
    Environ Sci Pollut Res Int; 2020 Aug; 27(24):30001-30019. PubMed ID: 32445152
    [TBL] [Abstract][Full Text] [Related]  

  • 5. An integrated approach based on artificial intelligence and novel meta-heuristic algorithms to predict demand for dairy products: a case study.
    Goli A; Khademi-Zare H; Tavakkoli-Moghaddam R; Sadeghieh A; Sasanian M; Malekalipour Kordestanizadeh R
    Network; 2021 Feb; 32(1):1-35. PubMed ID: 33390063
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Optimal design of groundwater pollution monitoring network based on a back-propagation neural network surrogate model and grey wolf optimizer algorithm under uncertainty.
    Guo X; Luo J; Lu W; Dong G; Pan Z
    Environ Monit Assess; 2024 Jan; 196(2):132. PubMed ID: 38200367
    [TBL] [Abstract][Full Text] [Related]  

  • 7. 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]  

  • 8. Evaluate effect of 126 pre-processing methods on various artificial intelligence models accuracy versus normal mode to predict groundwater level (case study: Hamedan-Bahar Plain, Iran).
    Saroughi M; Mirzania E; Achite M; Katipoğlu OM; Al-Ansari N; Vishwakarma DK; Chung IM; Alreshidi MA; Yadav KK
    Heliyon; 2024 Apr; 10(7):e29006. PubMed ID: 38601575
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Application of artificial intelligence models for prediction of groundwater level fluctuations: case study (Tehran-Karaj alluvial aquifer).
    Vadiati M; Rajabi Yami Z; Eskandari E; Nakhaei M; Kisi O
    Environ Monit Assess; 2022 Jul; 194(9):619. PubMed ID: 35904687
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Bee-inspired insights: Unleashing the potential of artificial bee colony optimized hybrid neural networks for enhanced groundwater level time series prediction.
    Katipoğlu OM; Mohammadi B; Keblouti M
    Environ Monit Assess; 2024 Jul; 196(8):724. PubMed ID: 38990407
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Development of artificial intelligence models for well groundwater quality simulation: Different modeling scenarios.
    Shiri N; Shiri J; Yaseen ZM; Kim S; Chung IM; Nourani V; Zounemat-Kermani M
    PLoS One; 2021; 16(5):e0251510. PubMed ID: 34043648
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Developing a fuzzy neural network-based support vector regression (FNN-SVR) for regionalizing nitrate concentration in groundwater.
    Hosseini SM; Mahjouri N
    Environ Monit Assess; 2014 Jun; 186(6):3685-99. PubMed ID: 24493265
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Combining data-intelligent algorithms for the assessment and predictive modeling of groundwater resources quality in parts of southeastern Nigeria.
    Egbueri JC; Agbasi JC
    Environ Sci Pollut Res Int; 2022 Aug; 29(38):57147-57171. PubMed ID: 35349055
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Application of machine learning in groundwater quality modeling - A comprehensive review.
    Haggerty R; Sun J; Yu H; Li Y
    Water Res; 2023 Apr; 233():119745. PubMed ID: 36812816
    [TBL] [Abstract][Full Text] [Related]  

  • 15. An efficient strategy for predicting river dissolved oxygen concentration: application of deep recurrent neural network model.
    Moghadam SV; Sharafati A; Feizi H; Marjaie SMS; Asadollah SBHS; Motta D
    Environ Monit Assess; 2021 Nov; 193(12):798. PubMed ID: 34773156
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Data-driven soft computing modeling of groundwater quality parameters in southeast Nigeria: comparing the performances of different algorithms.
    Egbueri JC; Agbasi JC
    Environ Sci Pollut Res Int; 2022 May; 29(25):38346-38373. PubMed ID: 35079969
    [TBL] [Abstract][Full Text] [Related]  

  • 17. 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]  

  • 18. Spatiotemporal assessment of groundwater quality and quantity using geostatistical and ensemble artificial intelligence tools.
    Nourani V; Ghaffari A; Behfar N; Foroumandi E; Zeinali A; Ke CQ; Sankaran A
    J Environ Manage; 2024 Mar; 355():120495. PubMed ID: 38432009
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Evaluation of geostatistical techniques and their hybrid in modelling of groundwater quality index in the Marand Plain in Iran.
    Rostami AA; Isazadeh M; Shahabi M; Nozari H
    Environ Sci Pollut Res Int; 2019 Dec; 26(34):34993-35009. PubMed ID: 31659709
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Performance evaluation of artificial intelligence paradigms-artificial neural networks, fuzzy logic, and adaptive neuro-fuzzy inference system for flood prediction.
    Tabbussum R; Dar AQ
    Environ Sci Pollut Res Int; 2021 May; 28(20):25265-25282. PubMed ID: 33453033
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 14.