Safety Evaluation on Building Construction Based on Hopfield Neural Network

DOI

10.2991/iccahe-16.2016.2How to use a DOI?

Keywords

Building construction; safety evaluation; indicator system; Hopfield neural network

Abstract

In view of the current problems in the process of implementing safety management system in building construction in our country, one model was established for safety evaluation on building construction with taking expert scoring as network input, security class as the output based on Hopfield neural network. It obtained security class II for a certain construction company, and it was consistent with the construction company's actual situation. Research shows that Hopfield neural network has very strong memory and association function, and reflects the digital characteristics of sample data. It is simple, convenient, fair, accurate and suitable for safety evaluation on building construction.

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Huiqin Gao
PY  - 2016/10
DA  - 2016/10
TI  - Safety Evaluation on Building Construction Based on Hopfield Neural Network
BT  - Proceedings of the 2016 5th International Conference on Civil, Architectural and Hydraulic Engineering (ICCAHE 2016)
PB  - Atlantis Press
SP  - 9
EP  - 15
SN  - 2352-5401
UR  - https://doi.org/10.2991/iccahe-16.2016.2
DO  - 10.2991/iccahe-16.2016.2
ID  - Gao2016/10
ER  -