Application of Artificial Neural Network on Cost Estimate of Architectural Construction
Date Issued
2010
Date
2010
Author(s)
Huang, Ting-Chien
Abstract
During initial phase of construction project, accuracy of cost estimate, which plays greatly important role, can be beneficially crucial along decision-making process among interest bodies. Accurate cost estimate may lower risk provided incomplete scope of information as well as undefined project goal.
Cost estimation on construction project relies substantially on experiential base of information, such as experience judgment method, factor estimation method, statistical theory…, etc. Until recent years, neural network algorithms, which represents thinking ways of human beings achieved by computational simulation, has been widely applied on research on extensive fields, including cost estimation on construction project.
This thesis established one cost estimate model with application of "back propagation algorithm" of artificial neural networks. Based on existing construction project cases, from which initial phase twelve informal variables were defined as input along computation whereas the project cost were divided into ten main items. Cost estimate can be fast and accurately achieved facilitated by self-analytical development of artificial neural networks and through amendment of the input variables. In conclusion, the application of artificial neural networks satisfies the accuracy of cost estimation and the assessment of rate of profit during initial phase of construction project.
Subjects
Artificial Neural Network
Back-propagation
Cost Estimate
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