Using fuzzy neural network approach to estimate contractors' markup

Min Liu, Yean Yng Ling

Research output: Contribution to journalArticlepeer-review

32 Scopus citations

Abstract

This paper presents a decision aid to assist contractors to estimate markup percentage to be included in their tenders, based on the Fuzzy neural network (FNN) approach. With the fuzzy logic inference system integrated inside, the FNN model provides users with a clear explanation to justify the rationality of the estimated markup output. Meanwhile, as every output of the FNN model is produced through the fuzzy inference rules, the results from the FNN model are in a reasonable and acceptable scale. By using this model, the difficulties in markup estimation due to its heuristic nature can be overcome.

Original languageEnglish (US)
Pages (from-to)1303-1308
Number of pages6
JournalBuilding and Environment
Volume38
Issue number11
DOIs
StatePublished - Nov 2003
Externally publishedYes

Keywords

  • Artificial neural network
  • Construction management
  • Fuzzy neural network
  • Markup
  • Tender estimating

ASJC Scopus subject areas

  • Environmental Engineering
  • Civil and Structural Engineering
  • Geography, Planning and Development
  • Building and Construction

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