Labor productivity modeling with neural networks


Rowings Jr. J. E. , Sonmez R.

Proceedings of the 1996 40th Annual Meeting of AACE International, Vancouver, Canada, 23 - 26 June 1996 identifier

  • Publication Type: Conference Paper / Full Text
  • Volume:
  • City: Vancouver
  • Country: Canada

Abstract

Regression analysis has been the common tool used in construction productivity studies, but in recent years, neural networks have been a successful alternative to regression analysis for other problems similar to construction labor productivity modeling. However, the potential capabilities of neural networks for construction labor productivity modeling have not been examined. This paper discusses the development of multivariate productivity models for concrete pouring by regression analysis and neural networks.