A Research of Cement Energy-Saving KM System Based on CBR and BP Neural Network

Abstract

The level of enterprise knowledge management is becoming an important means to measure their competitiveness. Inside the cement companies, the efficient and comprehensive management is come from the encoded data with a high degree of structure. But for that hard-to-codified tacit knowledge, the enterprise lacks of effective organization. This paper analyzes the advantages of case-based reasoning and BP neural network in case retrieval, and combines the features respectively to design the BP-CBR case retrieval model. The model joins BP neural network technology to the case organization index and retrieval stage of case-based reasoning, which makes up for the defect of traditional case-based reasoning. Through using the retrieval instance of a cement energy program, it verifies the effective application of knowledge management in the field of energy-saving reconstruction.

Keywords

• Cement enterprise
• Knowledge management
• Energy-saving reconstruction
• Case-based reasoning
• BP neural network