Reducing Octane Number Loss in Gasoline Refining Process by Using the Improved Sparrow Search Algorithm
Gasoline is the primary fuel used in small cars, and the exhaust emissions from gasoline combustion have a significant impact on the atmosphere. Efforts to clean up gasoline have therefore focused primarily on reducing the olefin and sulfur content of gasoline, while maintaining as much of the octane content as possible. With the aim of minimizing the loss of octane, this study investigated various machine learning algorithms to identify the best self-fitness function. An improved octane loss optimization model was developed, and the best octane loss calculation algorithm was identified.