The use of artificial neural networks for identifying sustainable biodiesel feedstocks
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![Table 2. Second-generation biodiesel feedstock containing at least 40% oil by dry weight [13–16,53,56–58]](https://thumb-us.123doks.com/thumbv2/123dok_us/161028.38172/9.595.62.550.228.656/table-second-generation-biodiesel-feedstock-containing-oil-weight.webp)
![Figure 4. Acid pre-esterification [60].](https://thumb-us.123doks.com/thumbv2/123dok_us/161028.38172/12.595.75.523.491.769/figure-acid-pre-esterification.webp)
![Figure 5. Fatty acid profile of various biodiesel fuels [31,73,74,76–79].](https://thumb-us.123doks.com/thumbv2/123dok_us/161028.38172/13.595.81.511.106.372/figure-fatty-acid-profile-various-biodiesel-fuels.webp)
![Table 5. International biodiesel standards [74,80].](https://thumb-us.123doks.com/thumbv2/123dok_us/161028.38172/14.595.65.527.455.765/table-international-biodiesel-standards.webp)
![Figure 7. Schematic diagram of a typical diesel engine fuel system [12].](https://thumb-us.123doks.com/thumbv2/123dok_us/161028.38172/20.595.50.560.449.679/figure-schematic-diagram-typical-diesel-engine-fuel.webp)
![Figure 11. Comparison of the performance of between ANN and various linear and non-linear prediction techniques [164]](https://thumb-us.123doks.com/thumbv2/123dok_us/161028.38172/25.595.142.452.425.616/figure-comparison-performance-various-linear-linear-prediction-techniques.webp)
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