ANN-based mark-up estimation system with self-explanatory capacities

Heng Li, L. Y. Shen, P. E.D. Love

Research output: Journal article publicationJournal articleAcademic researchpeer-review

57 Citations (Scopus)

Abstract

Artificial neural networks (ANNs) have been applied to support construction mark-up estimation. The major drawback of this application, however, is that an ANN system is unable to explain why and how a particular recommendation is made. This significantly affects the user-acceptance of the system and its results. The research presented in this paper investigates the use of the KT-1 method for automatically extracting rules from a trained neural network. The KT-1 method is implemented and tested on collected bidding data, and the results from the investigation indicate the usefulness of the KT-1 method. Discussions on the difficulties of generating automated explanations are also presented.
Original languageEnglish
Pages (from-to)185-189
Number of pages5
JournalJournal of Construction Engineering and Management
Volume125
Issue number3
DOIs
Publication statusPublished - 1 May 1999

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Building and Construction
  • Industrial relations
  • Strategy and Management

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