Bhokha, S and Ogunlana, S O (1999) Application of artificial neural network to forecast construction duration of buildings at the pre-design stage. Engineering, Construction and Architectural Management, 6(2), pp. 133-144. ISSN 0969-9988
Abstract
The application of an artificial neural network (ANN) to forecast the construction duration of buildings at the predesign stage is described in this paper. A three-layered back-propagation (BP) network consisting of 11 input nodes has been constructed. Ten binary input nodes represent basic information on building features (i.e. building function, structural system, foundation, height, exterior finishing, quality of interior decorating, and accessibility to the site), and one real-value input represents functional area. The input nodes are fully connected to one output node through hidden nodes. The network was implemented on a Pentium-150 based microcomputer using a neurocomputer program written in C+ +. The Generalized Delta Rule (GDR) was used as learning algorithm. One hundred and thirty-six buildings built during the period 1987 95 in the Greater Bangkok area were used for training and testing the network. The determination of the optimum number of hidden nodes, learning rate, and momentum were based on trial-and-error. The best network was found to consist of six hidden nodes, with a learning rate of 0.6, and null momentum. It was trained for 44700 epochs within 943 s such that the mean squared error (judgement) of training and test samples were reduced to 1.17 10-7 and 3.10 10-6, respectively. The network can forecast construction du-ration at the predesign stage with an average error of 13.6%.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | artificial neural network; back-propagation; duration estimation; generalized delta rule; predesign stage; supervised training and testing |
| Index terms: | estimation, design stage, propagation, program, accessibility, testing, duration, learning algorithm, artificial neural network |
| Subjects: | engineering process, professional practice, inclusive design, financial and cost management, algorithms, project controls, software systems, modelling and simulation |
| Topics: | Time Control, Engineering Principles, Design Practice, Cost Management, Research Practice, Digital Applications |
| Descriptive scope: | 2 PC |
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