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Evaluation of Predictive Capabilities of Regression Models and Artificial Neural Networks for Density and Viscosity Measurements of Different Biodiesel-Diesel-Vegetable Oil Ternary Blends

Authors: Gulum, Mert; Onay, Funda; Bilgin, Atilla;

Evaluation of Predictive Capabilities of Regression Models and Artificial Neural Networks for Density and Viscosity Measurements of Different Biodiesel-Diesel-Vegetable Oil Ternary Blends

Abstract

These figures and tables are related to the article "Evaluation of Predictive Capabilities of Regression Models and Artificial Neural Networks for Density and Viscosity Measurements of Different Biodiesel-Diesel-Vegetable Oil Ternary Blends" published in "Environmental and Climate Technologies". The article was performed by Mert Gulum (corresponding author), Funda Onay and Atilla Bilgin. Mert Gulum: mertgulumm@gmail.com / gulum@ktu.edu.tr / Karadeniz Technical University, Mechanical Engineering Depart. Trabzon / Turkey

In this section, it was given that Annex Figures and Annex Tables related to the article "Evaluation of Predictive Capabilities of Regression Models and Artificial Neural Networks for Density and Viscosity Measurements of Different Biodiesel-Diesel-Vegetable Oil Ternary Blends" published in "Environmental and Climate Technologies" journal.

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Keywords

Renewable energy; Biodiesel; Ethyl ester; Viscosity; Density; Prediction; Rational model; Exponential model; Artificial neural networks

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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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