The role of neural networks in early stage cost estimation in the 21st century

Anthony Harding, David Lowe, Margaret Emsley, Adam Hickson, Roy Duff, D Baldry, L Ruddock

Research output: Chapter in Book/Report/Conference proceedingConference contribution


The impact of technology on all areas of science and industry in the latter half of the twentieth century has been enormous, and the building industry has been no exception. However, early stage cost estimation has been little affected by these advances in comparison to most of the rest of the industry, and is still largely based on a combination of simple models and professional judgement. This paper reports how research currently being undertaken at UMIST could change this practice significantly. A neural network model which is able to estimate the total cost of construction to the client is being developed. This model considers forty variables which define the project at this early stage. Some of these variables would not usually be considered within the estimation of the cost. Perhaps most significantly, by including procurement it is able to evaluate the cost of different procurement routes inclusive of the client’s administrative costs. How the neural network improves on existing modelling techniques by its use of existing project data is explained, and its role in early stage cost estimation in the 21st century outlined.
Original languageEnglish
Title of host publicationProceedings of the RICS Construction and Building Research Conference
EditorsD Baldry, L Ruddock
Place of PublicationUnited Kingdom
PublisherRoyal Institution of Chartered Surveyors
Number of pages8
ISBN (Print)1-85406-968-2
Publication statusPublished - 1999


  • cost modelling
  • early stage estimating
  • neural networks
  • procurement


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