Murtaza, M B (1993) A decision support model integrating neural networks and an expert system for construction modularization. PhD thesis, University of Houston, USA.
Abstract
Modular construction is a method for constructing units of a project remote from the final project site. It brings the advantage of the manufacturing processes to the construction industry. It presents an opportunity to improve a variety of performance parameters relating to the project, such as, reduction of construction time, reduced labor costs, increased quality and efficiency, and simultaneous construction. The research performed has addressed the following issues of modularization, acquiring and structuring the knowledge of the experts in the field through knowledge engineering procedures, developing a decision model for modularization feasibility (pre-screening, detailed analysis and economic analysis), and developing a neural network system for modularization feasibility decision support. The original prototype system used a pure expert system approach. Based on various decision factors, it recommends an appropriate degree of construction modularization. If modularization is recommended, it also provides the user with an approximate change in costs and schedule due to modularization. The system is then trained using neural network approach, utilizing multi-layered unsupervised learning. This trained version of the system has some advantages over the initial expert system, such as the ability to generalize, performing better under incomplete information, and improving the basis of the initial expert system.
| Item Type: | Thesis (Doctoral) |
|---|---|
| Uncontrolled Keywords: | decision support; economic analysis; expert system; learning; manufacturing; modular construction; neural network |
| Index terms: | economic analysis, modular construction, expert system, neural network, prototype, decision support, construction industry, construction time, modularization, labour cost, manufacturing process, screening, efficiency |
| Subjects: | design analysis, building construction, manufacturing engineering, modelling and simulation, artificial intelligence, decision analysis, project controls, data management, cost management, industry analysis, performance management, management |
| Topics: | Engineering Principles, Procurement, Risk Management, Quality Management, Research Practice, Construction Technology, Human Resources, Digital Applications, Design Practice, Time Control |
| Descriptive scope: | 4 PCTA |
N.B. Descriptive scope is a count of how many of the five facets of empirical research are indicated by the words used in title, abstract and keywords. It is not intended as a judgement on the research; merely a count of the kind of word we would expect to indicate Phenomenon, Concepts, Theoretical framing, Empirical techniques, Analytical techniques. If all five are present, then a code of “5 PCTEA” will indicate this. If you feel the coding for this record is questionable, we welcome discussion around the terms we matched or the way we categorized them. The facet you would expect may not be coded, or a facet may be coded inappropriately. This can also bear on a larger question, of which facets should be treated as defining in construction management research. Please get in touch, and we will look at it. More details here