197 related articles for article (PubMed ID: 32876861)
1. Droplet size prediction in a microfluidic flow focusing device using an adaptive network based fuzzy inference system.
Mottaghi S; Nazari M; Fattahi SM; Nazari M; Babamohammadi S
Biomed Microdevices; 2020 Sep; 22(3):61. PubMed ID: 32876861
[TBL] [Abstract][Full Text] [Related]
2. 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]
3. 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]
4. Modeling water flux in osmotic membrane bioreactor by adaptive network-based fuzzy inference system and artificial neural network.
Hosseinzadeh A; Zhou JL; Altaee A; Baziar M; Li X
Bioresour Technol; 2020 Aug; 310():123391. PubMed ID: 32344239
[TBL] [Abstract][Full Text] [Related]
5. 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]
6. 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]
7. 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]
8. Performance comparison of wavelet neural network and adaptive neuro-fuzzy inference system with small data sets.
Tabaraki R; Khodabakhshi M
J Mol Graph Model; 2020 Nov; 100():107698. PubMed ID: 32739637
[TBL] [Abstract][Full Text] [Related]
9. 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]
10. 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]
11. Taxonomy of Adaptive Neuro-Fuzzy Inference System in Modern Engineering Sciences.
Chopra S; Dhiman G; Sharma A; Shabaz M; Shukla P; Arora M
Comput Intell Neurosci; 2021; 2021():6455592. PubMed ID: 34527042
[TBL] [Abstract][Full Text] [Related]
12. Evaluation of a new neutron energy spectrum unfolding code based on an Adaptive Neuro-Fuzzy Inference System (ANFIS).
Hosseini SA; Esmaili Paeen Afrakoti I
J Radiat Res; 2018 Jul; 59(4):436-441. PubMed ID: 29351656
[TBL] [Abstract][Full Text] [Related]
13. Prediction of oxidation parameters of purified Kilka fish oil including gallic acid and methyl gallate by adaptive neuro-fuzzy inference system (ANFIS) and artificial neural network.
Asnaashari M; Farhoosh R; Farahmandfar R
J Sci Food Agric; 2016 Oct; 96(13):4594-602. PubMed ID: 26909668
[TBL] [Abstract][Full Text] [Related]
14. ANFIS-based approach for the estimation of transverse mixing coefficient.
Ahmad Z; Azamathulla HM; Zakaria NA
Water Sci Technol; 2011; 63(5):1004-9. PubMed ID: 21411952
[TBL] [Abstract][Full Text] [Related]
15. [Study on diagnostic methods of breathing disorders based on fuzzy logic inference and the neural network].
Chen M; Yin X
Zhongguo Yi Liao Qi Xie Za Zhi; 2011 Jul; 35(4):260-2. PubMed ID: 22097748
[TBL] [Abstract][Full Text] [Related]
16. Development of a neuro-fuzzy technique for automated parameter optimization of inverse treatment planning.
Stieler F; Yan H; Lohr F; Wenz F; Yin FF
Radiat Oncol; 2009 Sep; 4():39. PubMed ID: 19781059
[TBL] [Abstract][Full Text] [Related]
17. 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]
18. Application of adaptive neuro-fuzzy inference system for epileptic seizure detection using wavelet feature extraction.
Subasi A
Comput Biol Med; 2007 Feb; 37(2):227-44. PubMed ID: 16480706
[TBL] [Abstract][Full Text] [Related]
19. 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]
20. Predictive modeling of copper (II) adsorption from aqueous solutions by sawdust: a comparative analysis of adaptive neuro-fuzzy interference system (ANFIS) and artificial neural network (ANN) approaches.
Claude BJ; Onyango MS
J Environ Sci Health A Tox Hazard Subst Environ Eng; 2024; 59(4):172-179. PubMed ID: 38613163
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]