Concrete slump prediction modeling with a fine-tuned convolutional neural network: hybridizing sea lion and dragonfly algorithms-Reference-Cited by-同舟云学术

Concrete slump prediction modeling with a fine-tuned convolutional neural network: hybridizing sea lion and dragonfly algorithms

Published:2021-01-22 Issue: Volume: Page:
ISSN:0944-1344
Container-title:Environmental Science and Pollution Research
language:en
Short-container-title:Environ Sci Pollut Res

Author:

Shaswat Kumar

Publisher

Springer Science and Business Media LLC

Subject

Health, Toxicology and Mutagenesis,Pollution,Environmental Chemistry,General Medicine

Link

http://link.springer.com/content/pdf/10.1007/s11356-020-12244-3.pdf

Reference45 articles.

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3. Agudelo, Isabel (2009) Supply chain management in the cement industry. PhD diss, Massachusetts Institute of Technology

4. Amlashi AT, Abdollahi SM, Goodarzi S, Ghanizadeh AR (2019) Soft computing based formulations for slump, compressive strength, and elastic modulus of bentonite plastic concrete. J Clean Prod 230:1197–1216

5. Bayar G, Bilir T (2019) A novel study for the estimation of crack propagation in concrete using machine learning algorithms. Constr Build Mater 215:670–685

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