Mining approximate dependencies from diesel engine assembling data using clustering-based rough sets theory
Wenbing Chang, Chunyu Gao, Yiyong Xiao, Shenghan Zhou · 2016
The assembly quality of diesel engine is one of the important factors affecting the quality of diesel engine. Diesel engine assembly clearance is a key factor affecting the quality of diesel engine assembling. In this paper, the data source is the assembling clearance parameters of a kind of domestic diesel engine. By studying the theory of clustering-based rough sets theory, a decision system which is based on rough sets and k-means clustering algorithm is established to dig up the approximate dependencies between assembling clearance parameters and quality level of diesel engine.