AI grey box model for alum sludge as a soil stabilizer: an accurate predictive tool-Reference-Cited by-同舟云学术

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AI grey box model for alum sludge as a soil stabilizer: an accurate predictive tool

Published:2023-05-28 Issue:5 Volume:17 Page:480-494
ISSN:1938-6362
Container-title:International Journal of Geotechnical Engineering
language:en
Short-container-title:International Journal of Geotechnical Engineering

Author:

Baghbani Abolfazl¹²^ORCID,Nguyen Minh Duc¹,Kafle Bidur¹,Baghbani Hasan³,Shirani Faradonbeh Roohollah⁴

Affiliation:

1. School of Engineering, Deakin University, Geelong, Australia

2. Future Regions Research Centre (FRRC), Federation University, Gippsland, Australia

3. School of Engineering, Ferdowsi University, Mashhad, Iran

4. Energy and Chemical Engineering, Curtin University, Kalgoorlie, WA, Australia, WA School of Mines Minerals

Publisher

Informa UK Limited

Subject

Soil Science,Geotechnical Engineering and Engineering Geology,Environmental Engineering

Link

https://www.tandfonline.com/doi/pdf/10.1080/19386362.2023.2258749

Reference41 articles.

1. Performance Evaluation of Sustainable Soil Stabilization Process Using Waste Materials

2. Ultrasonic Characterization of Compacted Salty Kaolin–Sand Mixtures Under Nearly Zero Vertical Stress Using Experimental Study and Machine Learning

3. Accurately Predicting Quartz Sand Thermal Conductivity Using Machine Learning and Grey-Box AI Models

4. Application of artificial intelligence in geotechnical engineering: A state-of-the-art review

5. Effects of particle shape on shear modulus of sand using dynamic simple shear testing

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Discussion of ‘Strength Evaluation of Expansive Soil Stabilized with Lead–Zinc Mine Tailings and Cement: An Artificial Intelligence Approach’ [DOI: 10.1007/s42947-024–00450-y];International Journal of Pavement Research and Technology;2024-08-06

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