A fuzzy neural approach for diagnosing PCM executing problems

Author

Chuang, Chin-Chang ; Tsai, Chia-Chang

Author_Institution

Dept. of Constr. Eng., National Taiwan Univ. of Sci. & Technol., Taipei, Taiwan

fYear

2005

fDate

4/29/2005 12:00:00 AM

Firstpage

171

Lastpage

176

Abstract

This study made a complete survey in professional construction management (PCM) of Taiwan, generalizing 6 critical executing problems in plan and 15 in design. Based on the characteristics of PCM back-propagation neural network (BPNN) and knowledge-based fuzzy neural network (KBFNN), the PCM planning and designing executing problems (PDEP) knowledge base was created for analyzing the causal relationships between these problems and their influence on overall goals of projects. This result indicates that the primary executing problem in planning stage is improper selection of design consultants. Finally, the PCM executing problems diagnosis system was created with access to serve as references to PCM consultants in project management.

Keywords

backpropagation; causality; construction; construction industry; diagnostic expert systems; fuzzy neural nets; project management; Access; PCM consultants; PCM executing problem diagnosis system; PCN1 backpropagation neural network; Planning and Designing Executing Problems knowledge base; Taiwan; causal relationships; fuzzy neural approach; knowledge-based fuzzy neural network; professional construction management; project management; Content management; Design engineering; Engineering management; Government; Knowledge management; Law; Neural networks; Phase change materials; Project management; Technology management;

fLanguage

English

Publisher

ieee

Conference_Titel

Systems and Information Engineering Design Symposium, 2005 IEEE

Print_ISBN

0-9744559-4-6

Type

conf

DOI

10.1109/SIEDS.2005.193254

Filename

1497147