Prediction for Mechanical Performance of Cold Rolled Ribbed Steel Bars Based on BP Neural Network with Dividing Variable Space According to Original Materials’ Tensile Strength

DOI

10.2991/icadme-15.2015.76How to use a DOI?

Keywords

Cold rolled ribbed steel bars, Mechanical performance, BP network

Abstract

This paper proposes a predictable method for mechanical performance of cold rolled ribbed steel bars based on BP network with dividing variable space according to original materials’ tensile strength. It builds a sample variable space partitioning model according to the original materials’ tensile strength. It also studies the performance prediction of cold rolled ribbed steel bars based on the 4-in & 1-out BP network and the performance prediction of cold rolled ribbed steel bars based on the 4-in & 2-out BP network. The results show that this method can reliably predict the mechanical performance of cold rolled ribbed steel bars, and the predictive effect of the 4-in & 1-out BP network model based on dividing variable space according to original materials’ tensile strength is superior to the 4-in & 2-out BP network model.

Copyright

© 2015, 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  - Bangsheng Xing
AU  - Le Xu
PY  - 2015/10
DA  - 2015/10
TI  - Prediction for Mechanical Performance of Cold Rolled Ribbed Steel Bars Based on BP Neural Network with Dividing Variable Space According to Original Materials’ Tensile Strength
BT  - Proceedings of the 5th International Conference on Advanced Design and Manufacturing Engineering
PB  - Atlantis Press
SP  - 379
EP  - 382
SN  - 2352-5401
UR  - https://doi.org/10.2991/icadme-15.2015.76
DO  - 10.2991/icadme-15.2015.76
ID  - Xing2015/10
ER  -