BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

301 related articles for article (PubMed ID: 19520419)

  • 1. Daily suspended sediment concentration simulation using ANN and neuro-fuzzy models.
    Rajaee T; Mirbagheri SA; Zounemat-Kermani M; Nourani V
    Sci Total Environ; 2009 Aug; 407(17):4916-27. PubMed ID: 19520419
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Wavelet and ANN combination model for prediction of daily suspended sediment load in rivers.
    Rajaee T
    Sci Total Environ; 2011 Jul; 409(15):2917-28. PubMed ID: 21546062
    [TBL] [Abstract][Full Text] [Related]  

  • 3. A comparison of various artificial intelligence approaches performance for estimating suspended sediment load of river systems: a case study in United States.
    Olyaie E; Banejad H; Chau KW; Melesse AM
    Environ Monit Assess; 2015 Apr; 187(4):189. PubMed ID: 25787167
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Modeling flow and sediment transport in a river system using an artificial neural network.
    Yitian L; Gu RR
    Environ Manage; 2003 Jan; 31(1):122-34. PubMed ID: 12447580
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Development of river ecosystem models for Flemish watercourses: case studies in the Zwalm river basin.
    Goethals P; Dedecker A; Raes N; Adriaenssens V; Gabriels W; De Pauw N
    Meded Rijksuniv Gent Fak Landbouwkd Toegep Biol Wet; 2001; 66(1):71-86. PubMed ID: 15952431
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Analysis and prediction of flow from local source in a river basin using a Neuro-fuzzy modeling tool.
    Aqil M; Kita I; Yano A; Nishiyama S
    J Environ Manage; 2007 Oct; 85(1):215-23. PubMed ID: 17110016
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Estimation of suspended sediment concentrations using Terra MODIS: an example from the Lower Yangtze River, China.
    Wang JJ; Lu XX
    Sci Total Environ; 2010 Feb; 408(5):1131-8. PubMed ID: 20022078
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Comparison of artificial neural network and multiple linear regression in the optimization of formulation parameters of leuprolide acetate loaded liposomes.
    Arulsudar N; Subramanian N; Muthy RS
    J Pharm Pharm Sci; 2005 Aug; 8(2):243-58. PubMed ID: 16124936
    [TBL] [Abstract][Full Text] [Related]  

  • 9. ANN modelling of sediment concentration in the dynamic glacial environment of Gangotri in Himalaya.
    Singh N; Chakrapani GJ
    Environ Monit Assess; 2015 Aug; 187(8):494. PubMed ID: 26156315
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Identification of critical genes in microarray experiments by a Neuro-Fuzzy approach.
    Chen CF; Feng X; Szeto J
    Comput Biol Chem; 2006 Oct; 30(5):372-81. PubMed ID: 16987708
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Artificial intelligence in predicting bladder cancer outcome: a comparison of neuro-fuzzy modeling and artificial neural networks.
    Catto JW; Linkens DA; Abbod MF; Chen M; Burton JL; Feeley KM; Hamdy FC
    Clin Cancer Res; 2003 Sep; 9(11):4172-7. PubMed ID: 14519642
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Toward multi-day-ahead forecasting of suspended sediment concentration using ensemble models.
    Alizadeh MJ; Jafari Nodoushan E; Kalarestaghi N; Chau KW
    Environ Sci Pollut Res Int; 2017 Dec; 24(36):28017-28025. PubMed ID: 28993996
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Improving one-dimensional pollution dispersion modeling in rivers using ANFIS and ANN-based GA optimized models.
    Seifi A; Riahi-Madvar H
    Environ Sci Pollut Res Int; 2019 Jan; 26(1):867-885. PubMed ID: 30415370
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Adaptive neuro-fuzzy inference system (ANFIS): a new approach to predictive modeling in QSAR applications: a study of neuro-fuzzy modeling of PCP-based NMDA receptor antagonists.
    Buyukbingol E; Sisman A; Akyildiz M; Alparslan FN; Adejare A
    Bioorg Med Chem; 2007 Jun; 15(12):4265-82. PubMed ID: 17434739
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Development of water quality models for supporting NH3-N control in a dam regulated river.
    Chung SW; Kim JH
    Water Sci Technol; 2005; 52(12):83-90. PubMed ID: 16477974
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Adaptive neuro-fuzzy based modelling for prediction of air pollution daily levels in city of Zonguldak.
    Yildirim Y; Bayramoglu M
    Chemosphere; 2006 Jun; 63(9):1575-82. PubMed ID: 16310825
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Prediction of effect of natural antioxidant compounds on hazelnut oil oxidation by adaptive neuro-fuzzy inference system and artificial neural network.
    Yalcin H; Ozturk I; Karaman S; Kisi O; Sagdic O; Kayacier A
    J Food Sci; 2011 May; 76(4):T112-20. PubMed ID: 22417373
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Capability assessment of conventional and data-driven models for prediction of suspended sediment load.
    Kumar A; Tripathi VK
    Environ Sci Pollut Res Int; 2022 Jul; 29(33):50040-50058. PubMed ID: 35226265
    [TBL] [Abstract][Full Text] [Related]  

  • 19. A comparison of quantitative structure-activity relationships for the effect of benzoic and cinnamic acids on Listeria monocytogenes using multiple linear regression, artificial neural network and fuzzy systems.
    Ramos-Nino ME; Ramirez-Rodriguez CA; Clifford MN; Adams MR
    J Appl Microbiol; 1997 Feb; 82(2):168-76. PubMed ID: 12452590
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Suspended sediment estimation and analysis in river basins with rice paddy fields.
    Lapong E; Fujihara M; Izumi T; Hamagami K; Kakihara T; Kobayashi N
    Water Sci Technol; 2012; 66(5):918-26. PubMed ID: 22797217
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 16.