Labor productivity modeling with neural networks

Date

1996-01-01

Author

Rowings Jr., James E.
Sönmez, Rifat

Metadata

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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.

Subject Keywords

Neural networks, Productivity, Case-Based Reasoning, Concrete construction

URI

https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=0029698397&origin=inward
https://hdl.handle.net/11511/76198

Conference Name

Proceedings of the 1996 40th Annual Meeting of AACE International

Collections

Department of Civil Engineering, Conference / Seminar

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Citation Formats

J. E. Rowings Jr. and R. Sönmez, “Labor productivity modeling with neural networks,” 1996, Accessed: 00, 2021. [Online]. Available: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=0029698397&origin=inward.