Mechanical Properties Prediction of Cold Rolled Ribbed Bars based on Full Sample Space and BP Neural Network

DOI

10.2991/ifeesm-17.2018.293How to use a DOI?

Keywords

Whole variable space, BP neural network, Cold rolled ribbed steel bars, Mechanical properties

Abstract

This paper proposes a method of mechanical performance prediction of cold rolled ribbed steel bars based on BP neural network with whole variable space. It builds a whole variable space model and studies the mechanical performance prediction of cold rolled ribbed steel bars based on the 5-in & 1-out BP network and the mechanical performance prediction of cold rolled ribbed steel bars based on the 5-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 5-in & 1-out BP network model based on whole variable space is superior to the 5-in & 2-out BP network model.

Copyright

© 2018, 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  - 2018/02
DA  - 2018/02
TI  - Mechanical Properties Prediction of Cold Rolled Ribbed Bars based on Full Sample Space and BP Neural Network
BT  - Proceedings of the 2017 3rd International Forum on Energy, Environment Science and Materials (IFEESM 2017)
PB  - Atlantis Press
SP  - 1617
EP  - 1620
SN  - 2352-5401
UR  - https://doi.org/10.2991/ifeesm-17.2018.293
DO  - 10.2991/ifeesm-17.2018.293
ID  - Xing2018/02
ER  -