Compressive strength prediction of blast furnace slag-fly ash concrete based on GA-BP algorithm

Jianjun Dong; Hongyang Xie; Yu Dai; Jiaxin Zhai; Yiwen Dai

doi:10.1117/12.2627604

11 March 2022 Compressive strength prediction of blast furnace slag-fly ash concrete based on GA-BP algorithm

Jianjun Dong, Hongyang Xie, Yu Dai, Jiaxin Zhai, Yiwen Dai

Proceedings Volume 12160, International Conference on Computational Modeling, Simulation, and Data Analysis (CMSDA 2021); 121601P (2022) https://doi.org/10.1117/12.2627604
Event: International Conference on Computational Modeling, Simulation, and Data Analysis (CMSDA 2021), 2021, Sanya, China

Abstract

In order to predict the compressive strength of blast furnace slag-fly ash concrete more accurately, a GA-BP model for compressive strength prediction was developed by improving the initial weights and thresholds of BP neural network through genetic algorithm on MATLAB platform. The prediction results of artificial neural network (BP), random forest (RF), support vector machine (SVM), extreme learning machine (ELM) and multiple nonlinear regression (MnLR) were compared and analyzed, and the GA-BP model has obvious advantages in terms of prediction accuracy and model stability. Thus, it provides guidance for the quality assessment of blast furnace slag-fly ash concrete, which has important practical value.

Citation Download Citation

Jianjun Dong, Hongyang Xie, Yu Dai, Jiaxin Zhai, and Yiwen Dai "Compressive strength prediction of blast furnace slag-fly ash concrete based on GA-BP algorithm", Proc. SPIE 12160, International Conference on Computational Modeling, Simulation, and Data Analysis (CMSDA 2021), 121601P (11 March 2022); https://doi.org/10.1117/12.2627604

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available