Development of Machine Learning Algorithms for Application in Major Performance Enhancement in the Selective Catalytic Reduction (SCR) System

Machine learning is used in this study to deal with the reduction design period and major performance improvement of selective catalyst system. The system helps NOx emission diesel engine. existing methods for systems tend be inefficient, due layout changes that require modification when mounting a vehicle based on previously designed models. There are some factors can affect engine identified by applying an optimized design. Taguchi orthogonal array eight three levels main factors. distance urea injector, mixer, inflow angle exhaust gas, direction rotation mixer inside pipe, number blades, bending blade as involved. These also considered manufacturing established through machine learning. has advantage being more efficient compared other determining relationship between data each mutual factor. help reducing processing time, which further decrease cost analysis improve This shows results statistically significant p values cone length lower than 0.05.