Citations in impact factor journals
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Green fuel production from Pistacia Khinjuk and its engine test
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Machine learning technology in biodiesel research: A review Progress in Energy and Combustion Science |
Densities of ammonium and phosphonium based deep eutectic solvents: Prediction using artificial intelligence and group contribution techniques Thermochimica Acta |
Artificial Neural Networks for Accurate Prediction of Physical
Properties of Aqueous Quaternary Systems of Carbon Dioxide (CO2)-Loaded
4-(Diethylamino)-2-butanol and Methyldiethanolamine Blended with
Monoethanolamine Industrial & Engineering Chemistry Research Vol. 55, Issue 44, 11614, 2016 |
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Characterization of MgO nanocatalyst to produce biodiesel from goat fat using transesterification process 3 Biotech Vol. 9, Issue 11, , 2019 |
Prediction of Biodiesel Properties from Fatty Acid Composition using Linear Regression and ANN Techniques Indian Chemical Engineer Vol. 52, Issue 4, 347, 2010 |
Artificial neural networks: an efficient tool for modelling and
optimization of biofuel production (a mini review) Biotechnology & Biotechnological Equipment Vol. 31, Issue 2, 221, 2017 |
Prediction of density and kinematic viscosity of biodiesel by
artificial neural networks Energy Sources, Part A: Recovery, Utilization, and Environmental Effects |
Data-Based Sensing and Stochastic Analysis of Biodiesel
Production Process Energies Vol. 12, Issue 1, 63, 2018 |
The Use of Artificial Neural Networks for Identifying Sustainable
Biodiesel Feedstocks Energies Vol. 6, Issue 12, 3764, 2013 |
How to cite this article
Saeid Baroutian, Mohamed Kheireddine Aroua, Abdul Aziz Abdul Raman and Nik Meriam Nik Sulaiman, 2008. Estimation of Vegetable Oil-Based Ethyl Esters Biodiesel Densities Using Artificial Neural Networks. Journal of Applied Sciences, 8: 3005-3011.
DOI: 10.3923/jas.2008.3005.3011
URL: https://scialert.net/abstract/?doi=jas.2008.3005.3011
DOI: 10.3923/jas.2008.3005.3011
URL: https://scialert.net/abstract/?doi=jas.2008.3005.3011