Abstract
The current study looks at using waste-derived biodiesel as pilot fuel and waste-derived biogas as a gaseous fuel to power a diesel engine in dual-fuel mode. A new ensemble approach called Boosted Regression Trees (BRT) was utilized to model the performance and emissions of a variable compression ratio diesel engine. The model's input parameters were selected to be load, fuel injection time, and compression ratio. The BRT-based model was created based on experimental data to predict brake thermal efficiency (BTE), Biogas Fuel Ratio (BFR), NOx, CO, and HC. As indicated by correlation values ranging from 0.9947 to 0.9997, low Theil's values (0.081), and high Kling-Gupta efficiency (>98 percent), the suggested BRT model predicted performance and emission parameters with reasonable accuracy. The BRT model was compared to an ANN model under similar operating conditions. The BRT-based model outperformed the ANN-based model on all statistical metrics. The efficacy of BRT models was demonstrated further by employing a novelmethod of comparing prediction models using Taylor's diagram.
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