The Research On Approach Of Supply Chain Performance Intelligent Analysis Based On Machine Learning

Considering the fast development of manufacturing, enterprise merging and recombination, creating the agile, lean, green supply chain, which is based on analysis and dynamic monitoring, is the main obstacle of the internationalization for domestic large enterprises. A set of intelligent analysis method based on machine learning theory was proposed, according to the manufacturing complex supply chain performance problems and the path of KDD. In order to realize supply chain performance analysis automation and intelligence, the supply chain performance data quality control, the key factors of supply chain performance and supply chain performance management problem in extracting diagnosis reasoning are discussed in this study. The main research results are as following.(1) The supply chain performance data quality control was proposed. First, based on total data quality management theory, combining the sampling theory, a multi-stage closed-loop data quality control process has been given. Based on the missing data processing technology, decomposing matrix theory, and data mining technology, two kinds of effective imputation algorithm has been given, which based on the decomposition of the nonnegative matrices factorization and CART. The effectiveness of the algorithm is demonstrated by the numerical experiments.(2) An algorithm of supply chain key factors extraction based on selective ensemble of robust principal component was proposed. According to the complexity of the supply chain performance analysis and investigation data, based on the robust statistic theory, realize the projection pursuit of main component algorithm is stable. Based on Bagging selective ensemble learning algorithm, information fusion technology, realize the principal component analysis selective ensemble.(3) Application Bayesian network to realize supply chain performance diagnosis. Bayesian network construction methods based on fuzzy ISM and Vague set have been given. Through the Bayesian network learning algorithm, the supply chain performance of management problems of key factors affect path. The validity of the algorithm is verified through the analysis of the actual data and rough sets of comparison algorithm.(4) Typical domestic manufacturing supply chain performance modeling and analysis practice. Based on the theory and method propose in this paper, a supply chain performance intelligent is analyzed for a domestic engine manufacturing enterprise. By comparing the two kinds of methods of analysis results, the validity and feasibility of supply chain performance analysis is verified, and the automation and intelligence of supply chain performance can be realized. Based on parts of method proposed in this paper, the supply chain performance intelligence analysis system has been developed.