An explainable intelligent algorithm for the multiple performance prediction of cement-based grouting materials-Reference-Cited by-同舟云学术

An explainable intelligent algorithm for the multiple performance prediction of cement-based grouting materials

Published:2023-02 Issue: Volume:366 Page:130146
ISSN:0950-0618
Container-title:Construction and Building Materials
language:en
Short-container-title:Construction and Building Materials

Author:

Zhao Weijian,Feng Siyuan,Liu Jianxiang,Sun Bochao

Funder

National Natural Science Foundation of China

Zhejiang University

Publisher

Elsevier BV

Subject

General Materials Science,Building and Construction,Civil and Structural Engineering

Reference40 articles.

1. Seismic isolation using sliding-elastomer bearing pads;Guéraud;Nucl. Eng. Des.,1985

2. R. First, F. Goodwin, C. Adams, D. Termunde, Precision Grouting of Critical Rotating Equipment, in: Turbomachinery Laboratory, Texas A&M Engineering Experiment Station, 2018.

3. A review of conventional seismic retrofitting techniques for URM;ElGawady;in,2004

4. Investigating mechanical characteristics of aggregate structure for road materials;Ren;Int. J. Pavement Eng.,2022

5. Effects of mortar ratio on the properties of super early strength grouting materials by ternary complex system;Li;Constr. Build. Mater.,2017

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