A Data-Driven Influential Factor Analysis Method for Fly Ash–Based Geopolymer Using Optimized Machine-Learning Algorithms-Reference-Cited by-同舟云学术

A Data-Driven Influential Factor Analysis Method for Fly Ash–Based Geopolymer Using Optimized Machine-Learning Algorithms

Published:2022-07 Issue:7 Volume:34 Page:
ISSN:0899-1561
Container-title:Journal of Materials in Civil Engineering
language:en
Short-container-title:J. Mater. Civ. Eng.

Author:

Ma Guowei¹,Cui Aidi²,Huang Yimiao³,Dong Wei⁴^ORCID

Affiliation:

1. Professor, Dept. of Civil and Transportation Engineering, Hebei Univ. of Technology, Tianjin 300401, China.

2. Postgraduate, Dept. of Civil and Transportation Engineering, Hebei Univ. of Technology, Tianjin 300401, China.

3. Professor, Dept. of Civil and Transportation Engineering, Hebei Univ. of Technology, Tianjin 300401, China (corresponding author).

4. Ph.D. Candidate, Dept. of Civil, Environmental and Mining Engineering, Univ. of Western Australia, Perth 6009, Australia. ORCID: .

Publisher

American Society of Civil Engineers (ASCE)

Subject

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

Link

https://ascelibrary.org/doi/pdf/10.1061/%28ASCE%29MT.1943-5533.0004266

Reference57 articles.

1. Investigation to some Preliminary Geotechnical Properties of Soft Clay Stabilized by Fly Ash Based Geopolymers

2. Forecast flexural strength of pervious concrete by SVR

3. Compressive strength and workability characteristics of low-calcium fly ash-based self-compacting geopolymer concrete;Ahmed M. F.;Int. J. Environ. Eng.,2011

4. Massive data discrimination via linear support vector machines

5. Workability and strength of coarse high calcium fly ash geopolymer

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