Construction Knowledge Mining and Application of Generalized Fuzzy Network in Construction Decision Management.

摘要

In the trend of globalization and informatization, the construction enterprises are facing the fierce competitions from domestic and foreign markets and the profound changes of the professionalization and informatization of management model, therefore, much challenges come about in the management capabilities and domain knowledge of traditional organization. As knowledge is an important asset of construction industry, a central theme of the competitiveness enhancing in construction enterprises is knowledge management. Because of the organization structure dispersity of construction enterprises and the individual uniqueness of construction projects, knowledge management planning and implementation in the construction enterprises must be a complex and complicated process.;Data mining is a key part of knowledge management. The application of data mining algorithms to explore the potential relationships from masses of data directly determines the level of efficiency of knowledge. The paper focus on the investigation of the relationship between related concepts, the research of data mining algorithm, the application of data mining based on knowledge management system of construction enterprises.;First, the paper describes the basic concepts of knowledge management, data mining, and the basic situations of construction industry and construction enterprises, investigates the relationship and function of data mining and knowledge management, key and hot issues of data mining algorithms, applications and construction enterprises knowledge management.;Second, the paper proposes the architecture of data mining module of construction enterprise. With the actual conditions of construction enterprises, plans six aspects of data mining model of construction enterprises based on cost, schedule, quality, safety, environmental protection and risk issues.;Third, the paper designed the generalized fuzzy network (GFN) algorithms and applications. The results of the experiments show that the GFN is more efficient and effective than similar algorithms.;Finally, the paper introduces the implementation and application of data mining module of construction enterprises.;The achievement of the paper is mainly reflected in the model, algorithm, application of data mining in construction enterprises knowledge management system, with a strong practical and guidance.;Key Words: construction industry, construction enterprises, knowledge management, knowledge management systems, data mining, data mining algorithms.