Application of Neural Network in Predicting the Strength of the Steel Fiber Reinforced Concrete at Minus Temperature

Liu Yongsheng; Xu Dongmei

Jul. 2021

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Article Navigation > GEOTECHNICAL ENGINEERING TECHNIQUE > 2005 > 19(5): 225-226,232

Liu Yongsheng, Xu Dongmei. Application of Neural Network in Predicting the Strength of the Steel Fiber Reinforced Concrete at Minus Temperature[J]. GEOTECHNICAL ENGINEERING TECHNIQUE, 2005, 19(5): 225-226,232.

Citation:

Liu Yongsheng, Xu Dongmei. Application of Neural Network in Predicting the Strength of the Steel Fiber Reinforced Concrete at Minus Temperature[J]. GEOTECHNICAL ENGINEERING TECHNIQUE, 2005, 19(5): 225-226,232.

Citation:

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Application of Neural Network in Predicting the Strength of the Steel Fiber Reinforced Concrete at Minus Temperature

Liu Yongsheng¹,
Xu Dongmei²

1. Department of Mechanics and Mechanical Engineering, University of Science and Technology of China, Hefei Anhui 230027;
2. Anhui Province Construction Supervision Company Limited, Hefei Anhui 230022 China

Received Date: 2005-06-27

Abstract

Abstract

The BP neural network is established to predict the compressive strength/the flexural strength, the tensile strength and the shear strength of steel fiber reinforced concrete at minus temperature. The checking results show that the BP network could predict the strengths successfully by establishing the appropriate non-linear model and studying.
- neural network,
- minus temperature,
- steel fiber reinforced concrete,
- stength,
- prediction