This study highlights the urgent need to improve the performance of biodiesel engines in light of the growing environmental challenges that are mostly brought on by a rise in vehicle usage. It introduces a novel approach by combining vegetable oil and hydrogen as an alternative fuel and using a Decision Elman Neural Framework (DENF) to adjust engine settings. Through the implementation of an all-inclusive strategy that includes data gathering, pre-processing, feature analysis, and real-time tracking, the system aims to increase engine performance while reducing environmental impact. A comparison with traditional techniques highlights the improved engine performance and reduced emissions that the suggested method achieves. Combining vegetable oil and hydrogen with DENF appears to be a key tactic for increasing engine efficiency and promoting sustainability in biodiesel engines. The data-driven approach results in a significant 7.4% improvement in engine performance and a 2.1% decrease in peak emissions. On the other hand, it is linked to a 19.8% increase in CO emissions and a 5.6% decrease in soot emissions, indicating better engine performance and a sustainable environment.
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