Data on artificial neural network and response surface methodology analysis of biodiesel production

Ayoola, A. A. and Hymore, F. K. and Omonhinmin, Conrad A. and Babalola, P.O. and Bolujo, E. O. and Adeyemi, Gideon Adewale and Babalola, Rasheed and OLAFADEHAN, O. A. (2020) Data on artificial neural network and response surface methodology analysis of biodiesel production. Data in Brief, 31. ISSN 2352-3409

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Abstract

The biodiesel production from waste soybean oil (using NaOH and KOH catalysts independently) was investigated in this study. The use of optimization tools (artificial neural network, ANN, and response surface methodology, RSM) for the modelling of the relationship between biodiesel yield and process parameters was carried out. The variables em- ployed in the experimental design of biodiesel yields were methanol-oil mole ratio (6 –12), catalyst concentration (0.7 –1.7 wt/wt%), reaction temperature (48 –62 °C) and reaction time (50 –90 min). Also, the usefulness of both the RSM and ANN tools in the accurate prediction of the regression mod- els were revealed, with values of R-sq being 0.93 and 0.98 for RSM and ANN respectively.

Item Type:	Article
Uncontrolled Keywords:	ANN Biodiesel KOH NaOH RSM Waste soybean oil
Subjects:	Q Science > QH Natural history > QH301 Biology T Technology > TJ Mechanical engineering and machinery T Technology > TP Chemical technology
Divisions:	Faculty of Engineering, Science and Mathematics > School of Engineering Sciences
Depositing User:	Mrs Patricia Nwokealisi
Date Deposited:	16 Jun 2020 14:28
Last Modified:	16 Jun 2020 14:28
URI:	http://eprints.covenantuniversity.edu.ng/id/eprint/13391

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