Prediction of Fe-Co-Mn/MgO Catalytic Activity in Fischer-Tropsch Synthesis Using Nu-support Vector Regression

Authors

Abstract:

Support vector regression (SVR) is a learning method based on the support vector machine (SVM) that can be used for curve fitting and function estimation. In this paper, the ability of the nu-SVR to predict the catalytic activity of the Fischer-Tropsch (FT) reaction is evaluated and the result is compared with two other prediction techniques including: multilayer perceptron (MLP) and subtractive clustering-adaptive neuro-fuzzy inference system (SUB-ANFIS). The Fischer-Tropsch synthesis (FTS) was studied in a fixed bed micro-reactor under different operating conditions. An extensive experimental data set of MgO supported Fe-Co-Mn catalyst was used to predict the FTS. The input variables of three aforesaid models were: reactor temperature, H2/CO ratio and total pressure, while the CO conversion (catalytic activity) was used as an output variable. Finally, the achieved results from these approaches were compared. The results reveal that thenu-SVR model has more accurate (MSE = 0.0014) than the MLP (MSE = 0.0097) and ANFIS (MSE = 0.0043) approaches.

Upgrade to premium to download articles

Sign up to access the full text

Already have an account?login

similar resources

prediction of fe-co-mn/mgo catalytic activity in fischer-tropsch synthesis using nu-support vector regression

support vector regression (svr) is a learning method based on the support vector machine (svm) that can be used for curve fitting and function estimation. in this paper, the ability of the nu-svr to predict the catalytic activity of the fischer-tropsch (ft) reaction is evaluated and the result is compared with two other prediction techniques including: multilayer perceptron (mlp) and subtractiv...

full text

Pilot scale study of Co-Fe-Ni nanocatalyst for CO hydrogenation in Fischer-Tropsch synthesis

In this work, a Co-Fe-Ni catalyst was prepared and the effect of a range of operational variables such as gas hourly space velocity (GHSV), calcination temperature, calcination time and agent on its catalytic performance for green-fuels production was investigated. By application of different characterization techniques such as XRD, BET, TGA/DSC, and SEM, it was found that these parameters have...

full text

preparation and characterization of new co-fe and fe-mn nano catalysts using resol phenolic resin and response surface methodology study for fischer-tropsch synthesis

کاتالیزورهای co-fe-resol/sio2و fe-mn-resol/sio2 با استفاده از روش ساده و ارزان قیمت همرسوبی تهیه شدند. از رزین پلیمری resol در فرآیند تهیه کاتالیزور استفاده شد.

comparison of catalytic activity of heteropoly compounds in the synthesis of bis(indolyl)alkanes.

heteropoly acids (hpa) and their salts have advantages as catalysts which make them both economically and environmentally attractive, strong br?nsted acidity, exhibiting fast reversible multi-electron redox transformations under rather mild conditions, very high solubility in polar solvents, fairly high thermal stability in the solid states, and efficient oxidizing ability, so that they are imp...

15 صفحه اول

Selective synthesis ofa-olefins on Fe-Zn Fischer-Tropsch catalysts

Fe/Zn oxides promoted with K and Cu selectively produce a-olefins at typical FischerTropsch synthesis conditions (2/1 H2/CO, 1 MPa, and 270°C). The simultaneous presence of K and Cu introduces a synergistic activity enhancement while maintaining the high oletrm selectivity obtained by alkali promotion. Structural and morphological differences in Fe-Zn oxides prepared from ammonium glycolate com...

full text

Correlation between Fischer-Tropsch catalytic activity and composition of catalysts

This paper presents the synthesis and characterization of monometallic and bimetallic cobalt and iron nanoparticles supported on alumina. The catalysts were prepared by a wet impregnation method. Samples were characterized using temperature-programmed reduction (TPR), temperature-programmed oxidation (TPO), CO-chemisorption, transmission electron microscopy (TEM), field emission scanning electr...

full text

My Resources

Save resource for easier access later

Save to my library Already added to my library

{@ msg_add @}


Journal title

volume 4  issue 3

pages  391- 405

publication date 2016-09-01

By following a journal you will be notified via email when a new issue of this journal is published.

Hosted on Doprax cloud platform doprax.com

copyright © 2015-2023