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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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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.