Application of artificial neural network to predict properties of diesel-biodiesel blends

Authors

  • Jatinder Kumar Department of Chemical and Bio Engineering, B R Ambedkar National Institute of Technology Jalandhar
  • Ajay Bansal Department of Chemical and Bio Engineering, B R Ambedkar National Institute of Technology Jalandhar

DOI:

https://doi.org/10.3126/kuset.v6i2.4017

Keywords:

Biodiesel, Artificial Neural Network, Principle of least squares, Diesel, Linear Regression

Abstract

The experimental determination of various properties of diesel-biodiesel mixtures is very time consuming as well as tedious process. Any tool helpful in estimation of these properties without experimentation can be of immense utility. In present work, other tools of determination of properties of diesel-biodiesel blends were tried. A traditional statistical technique of linear regression (principle of least squares) was used to estimate the flash point, fire point, density and viscosity of diesel and biodiesel mixtures. A set of seven neural network architectures, three training algorithms along with ten different sets of weight and biases were examined to choose best Artificial Neural Network (ANN) to predict the above-mentioned properties of dieselbiodiesel mixtures. The performance of both of the traditional linear regression and ANN techniques were then compared to check their validity to predict the properties of various mixtures of diesel and biodiesel.

Key words: Biodiesel; Artificial Neural Network; Principle of least squares; Diesel; Linear Regression.

DOI: 10.3126/kuset.v6i2.4017

Kathmandu University Journal of Science, Engineering and Technology Vol.6. No II, November, 2010, pp.98-103

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How to Cite

Kumar, J., & Bansal, A. (2010). Application of artificial neural network to predict properties of diesel-biodiesel blends. Kathmandu University Journal of Science, Engineering and Technology, 6(2), 98–103. https://doi.org/10.3126/kuset.v6i2.4017

Issue

Vol. 6 No. 2 (2010)

Section

Original Research Articles

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