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|Title:||Construction knowledge mining and application of generalized fuzzy network in construction decision management||Authors:||Zhou, Yuguang||Keywords:||Construction industry -- Management.
Data mining -- Mathematical models.
Hong Kong Polytechnic University -- Dissertations
|Issue Date:||2012||Publisher:||The Hong Kong Polytechnic University||Abstract:||With the trend of globalization and information technology, construction enterprises are facing fierce competition from domestic and foreign markets and profound changes in professional management model and information technology and their traditional organizational management capabilities and professional knowledge are being greatly challenged. Knowledge is an important asset of the construction industry, while knowledge management is a central subject in improving the competitiveness of enterprises. However, the organization dispersion of construction enterprises and uniqueness of individual construction project determine that knowledge management of construction enterprises is a complex systematic engineering. Data mining is a key part of the knowledge management system of construction enterprises and its essence lies in applying the data mining algorithms to explore the underlying data relationship in vast amounts of data, which directly determines the effectiveness of knowledge. This study focuses on the application of data mining in knowledge management system of construction enterprises, mainly studying on the relationship between data mining and knowledge management, researching on the data mining algorithm and exploring the data mining application based on knowledge management of construction enterprise.
Firstly, the study describes the basic concepts of knowledge management, knowledge management systems and data mining and basic situations of the construction industry and construction enterprises, and studies on the relationship between data mining and knowledge management and their roles, as well as the algorithm and applications of data mining and priorities and hot issues of knowledge management of construction enterprises. Secondly, this study proposes the system architecture of construction enterprise knowledge management, especially the details of data mining part. Combined with the actual situations of construction enterprises, it designs a data mining model for construction enterprises based on six major aspects of cost, schedule, quality, safety, environmental protection and risk. In addition, this study designs the algorithm and application of Generalized Fuzzy Network (GFN) combined with the data mining model of construction enterprises and characteristics of construction project data based on the latest research results of data mining algorithms. Experiments show that the generalized fuzzy network is superior in the efficiency and effectiveness compared with similar algorithms. Finally, the study describes the implementation and application of data mining part in the knowledge management system of construction enterprises. The data mining-based knowledge management system of construction enterprises shows the advantages of modular and network system architecture, and the necessity of application of data mining to the knowledge management system of construction enterprises. The research and application results of this thesis mainly lie in the realization of data mining mode, algorithm and application based on the knowledge management system with a strong practicability and guidance.
|Description:||ix, 202 p. : ill. (some col.) ; 30 cm.
PolyU Library Call No.: [THS] LG51 .H577P BRE 2012 Zhou
|URI:||http://hdl.handle.net/10397/5436||Rights:||All rights reserved.|
|Appears in Collections:||Thesis|
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