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 *

133 related articles for article (PubMed ID: 35902679)

  • 1. Application of machine learning for inter turn fault detection in pumping system.
    Dutta N; Kaliannan P; Shanmugam P
    Sci Rep; 2022 Jul; 12(1):12906. PubMed ID: 35902679
    [TBL] [Abstract][Full Text] [Related]  

  • 2. 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]  

  • 3. Comparative study of artificial neural network (ANN), adaptive neuro-fuzzy inference system (ANFIS) and multiple linear regression (MLR) for modeling of Cu (II) adsorption from aqueous solution using biochar derived from rambutan (Nephelium lappaceum) peel.
    Wong YJ; Arumugasamy SK; Chung CH; Selvarajoo A; Sethu V
    Environ Monit Assess; 2020 Jun; 192(7):439. PubMed ID: 32556670
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Solar radiation and solar energy estimation using ANN and Fuzzy logic concept: A comprehensive and systematic study.
    Patel D; Patel S; Patel P; Shah M
    Environ Sci Pollut Res Int; 2022 May; 29(22):32428-32442. PubMed ID: 35178628
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Fuzzy Inference System Approach for Locating Series, Shunt, and Simultaneous Series-Shunt Faults in Double Circuit Transmission Lines.
    Swetapadma A; Yadav A
    Comput Intell Neurosci; 2015; 2015():620360. PubMed ID: 26413088
    [TBL] [Abstract][Full Text] [Related]  

  • 6. 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]  

  • 7. Prediction of Attendance Demand in European Football Games: Comparison of ANFIS, Fuzzy Logic, and ANN.
    Şahin M; Erol R
    Comput Intell Neurosci; 2018; 2018():5714872. PubMed ID: 30158960
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Leuconostoc mesenteroides growth in food products: prediction and sensitivity analysis by adaptive-network-based fuzzy inference systems.
    Wang HY; Wen CF; Chiu YH; Lee IN; Kao HY; Lee IC; Ho WH
    PLoS One; 2013; 8(5):e64995. PubMed ID: 23705023
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Bubbly flow prediction with randomized neural cells artificial learning and fuzzy systems based on k-ε turbulence and Eulerian model data set.
    Babanezhad M; Pishnamazi M; Marjani A; Shirazian S
    Sci Rep; 2020 Aug; 10(1):13837. PubMed ID: 32796869
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Modeling daily water temperature for rivers: comparison between adaptive neuro-fuzzy inference systems and artificial neural networks models.
    Zhu S; Heddam S; Nyarko EK; Hadzima-Nyarko M; Piccolroaz S; Wu S
    Environ Sci Pollut Res Int; 2019 Jan; 26(1):402-420. PubMed ID: 30406582
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Effective modelling of hydrogen and energy recovery in microbial electrolysis cell by artificial neural network and adaptive network-based fuzzy inference system.
    Hosseinzadeh A; Zhou JL; Altaee A; Baziar M; Li D
    Bioresour Technol; 2020 Nov; 316():123967. PubMed ID: 32777721
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Research on air pollutant concentration prediction method based on self-adaptive neuro-fuzzy weighted extreme learning machine.
    Li Y; Jiang P; She Q; Lin G
    Environ Pollut; 2018 Oct; 241():1115-1127. PubMed ID: 30029320
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Artificial intelligence modeling to predict transmembrane pressure in anaerobic membrane bioreactor-sequencing batch reactor during biohydrogen production.
    Taheri E; Amin MM; Fatehizadeh A; Rezakazemi M; Aminabhavi TM
    J Environ Manage; 2021 Aug; 292():112759. PubMed ID: 33984638
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Multivariate data-based optimization of membrane adsorption process for wastewater treatment: Multi-layer perceptron adaptive neural network versus adaptive neural fuzzy inference system.
    Naghibi SA; Salehi E; Khajavian M; Vatanpour V; Sillanpää M
    Chemosphere; 2021 Mar; 267():129268. PubMed ID: 33338708
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Application of image processing and soft computing strategies for non-destructive estimation of plum leaf area.
    Sabouri A; Bakhshipour A; Poornoori M; Abouzari A
    PLoS One; 2022; 17(7):e0271201. PubMed ID: 35816484
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Application of classical and novel integrated machine learning models to predict sediment discharge during free-flow flushing.
    Javadi F; Qaderi K; Ahmadi MM; Rahimpour M; Madadi MR; Mahdavi-Meymand A
    Sci Rep; 2022 Nov; 12(1):19390. PubMed ID: 36371476
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Ensemble Dilated Convolutional Neural Network and Its Application in Rotating Machinery Fault Diagnosis.
    Cai Y; Wang Z; Yao L; Lin T; Zhang J
    Comput Intell Neurosci; 2022; 2022():6316140. PubMed ID: 36188683
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Wavelet packet and fuzzy logic theory for automatic fault detection in induction motor.
    Talhaoui H; Ameid T; Aissa O; Kessal A
    Soft comput; 2022; 26(21):11935-11949. PubMed ID: 35411204
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Machine learning accelerated approach to infer nuclear magnetic resonance porosity for a middle eastern carbonate reservoir.
    Mustafa A; Tariq Z; Mahmoud M; Abdulraheem A
    Sci Rep; 2023 Mar; 13(1):3956. PubMed ID: 36894553
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Simulative and experimental investigation on stator winding turn and unbalanced supply voltage fault diagnosis in induction motors using Artificial Neural Networks.
    Lashkari N; Poshtan J; Azgomi HF
    ISA Trans; 2015 Nov; 59():334-42. PubMed ID: 26412499
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 7.