ANFIS models for prediction of biodiesel fuels cetane number using desirability function

ANFIS models for prediction of biodiesel fuels cetane number using desirability function •ANFIS models are developed for predicting cetane number of biodiesel fuels from their FAMEs composition.•Number of double bonds (dn) and molar weight (Mw) of biodiesel fuels were used as input variables in models.•Predictive ability of ANFIS models were compared by statistical criteria of R2, RMSE, STD and MAPE.•Desirability functions coupled with multi-criteria for identifying the best ANFIS model. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Fuel Elsevier

ANFIS models for prediction of biodiesel fuels cetane number using desirability function

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Publisher
Elsevier
Copyright
Copyright © 2017 Elsevier Ltd
ISSN
0016-2361
D.O.I.
10.1016/j.fuel.2017.12.025
Publisher site
See Article on Publisher Site

Abstract

•ANFIS models are developed for predicting cetane number of biodiesel fuels from their FAMEs composition.•Number of double bonds (dn) and molar weight (Mw) of biodiesel fuels were used as input variables in models.•Predictive ability of ANFIS models were compared by statistical criteria of R2, RMSE, STD and MAPE.•Desirability functions coupled with multi-criteria for identifying the best ANFIS model.

Journal

FuelElsevier

Published: Mar 15, 2018

References

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