Title: Strength prediction of fibre nano concrete based on grey support vector machine

Authors: Yang Han

Addresses: Department of Civil Engineering, Zhengzhou College of Finance and Economics, Zhengzhou, 450000, China

Abstract: Because the traditional strength prediction method of fibre nano concrete has the problem of poor prediction effect, a strength prediction method of fibre nano concrete based on grey support vector machine (SVM) is proposed. The raw materials required for the preparation of fibre nano concrete are used as the initial strength prediction index of fibre nano concrete. After the prediction index data is not dimensionally processed, the grey correlation coefficient and grey correlation degree of the prediction index for the concrete strength are calculated. The prediction index with the grey correlation degree value higher than 0.6 is selected as the final prediction index. The SVM prediction model and grey prediction GN (1, 1) model are combined to obtain the final prediction results. The experimental results show that the strength prediction effect of the proposed method is good.

Keywords: prediction index; grey correlation degree; support vector machine; SVM; grey prediction; fibre nano; strength concrete.

DOI: 10.1504/IJMMP.2023.130574

International Journal of Microstructure and Materials Properties, 2023 Vol.16 No.5, pp.393 - 409

Received: 14 Oct 2022
Accepted: 30 Jan 2023
Published online: 28 Apr 2023 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article