Proceedings of the 2016 4th International Conference on Machinery, Materials and Computing Technology

Research on Estimation for Architectural Project Cost Based on BP Neural Network

Authors
Jing Zhao, Li Zhao, Yi-wei Ren
Corresponding Author
Jing Zhao
Available Online March 2016.
DOI
https://doi.org/10.2991/icmmct-16.2016.26How to use a DOI?
Keywords
Frame structure; BP neural network; Project cost; Cost index
Abstract
The estimation of project cost affects the rationality of project invitation for bid. According to the principles of construction budget estimate, the main character index is identified as a model example, and the char index is transformed into a numeric character index. At the same time, the BP neural network improved by gradient descent momentum and an adaptive learning rate is introduced to estimate the project cost which involved the cost index, and the prototype data is presented and analyzed in the neural network to establish the cost estimation model. The results show that the model is feasible and credible completely, the cost error of which is much better than that in the relevant document, and it could provide a more efficient path for fast estimating of the project cost.
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This is an open access article distributed under the CC BY-NC license.

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Volume Title
Proceedings of the 2016 4th International Conference on Machinery, Materials and Computing Technology
Series
Advances in Engineering Research
Publication Date
March 2016
ISBN
978-94-6252-165-0
ISSN
2352-5401
DOI
https://doi.org/10.2991/icmmct-16.2016.26How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Jing Zhao
AU  - Li Zhao
AU  - Yi-wei Ren
PY  - 2016/03
DA  - 2016/03
TI  - Research on Estimation for Architectural Project Cost Based on BP Neural Network
BT  - Proceedings of the 2016 4th International Conference on Machinery, Materials and Computing Technology
PB  - Atlantis Press
SP  - 137
EP  - 142
SN  - 2352-5401
UR  - https://doi.org/10.2991/icmmct-16.2016.26
DO  - https://doi.org/10.2991/icmmct-16.2016.26
ID  - Zhao2016/03
ER  -