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In this study, waste and discarded cooking oils (WCO) of palm, sunflower, rice bran and groundnut oils are collected from local restaurants. The high viscous WCO was converted into waste cooking oil biodiesel (WCOBD) by a single-stage transesterification process. During the transesterification process, the important parameters which show a significant change in biodiesel yield are studied using the optimization tool of response surface methodology (RSM). Results reported that 91.30% biodiesel yield was achieved within L18 experiments and NaOH catalyst was identified as the most influential parameter on WCOBD yield. Artificial Intelligence (AI) based modeling was also carried out to predict biodiesel yield. From AI modeling, a predicted yield of 92.88% was achieved, which is 1.70% higher than the RSM method. These results reveal the prediction capabilities and accuracy of the chosen modeling and optimization methods. In addition, the significant fuel properties are measured and observed within the scope of ASTM standards (ASTMD6751) and fatty acid profiles from chromatography reveal the presence of high unsaturated fatty acids in WCOBD. Therefore, utilizing the waste cooking oils for biodiesel production can mitigate the global challenges of environmental and energy paucity.
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