Mechanical properties evaluation of waste gangue-based cemented backfill materials based on an improved response surface model-Reference-Cited by-同舟云学术

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Mechanical properties evaluation of waste gangue-based cemented backfill materials based on an improved response surface model

Published:2023-12-11 Issue:2 Volume:31 Page:3076-3089
ISSN:1614-7499
Container-title:Environmental Science and Pollution Research
language:en
Short-container-title:Environ Sci Pollut Res

Author:

Shi Peitao,Zhang Jixiong,Yan Hao,Zhou Nan,Zhu Gaolei,Zhao Yang,Chen Peng

Funder

Natural Science Foundation of Jiangsu Province

National Natural Science Foundation of China

Ordos Science & Technology Plan

Postgraduate Research & Practice Innovation Program of Jiangsu Province

Publisher

Springer Science and Business Media LLC

Subject

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

Link

https://link.springer.com/content/pdf/10.1007/s11356-023-31368-w.pdf

Reference67 articles.

1. Arora S, Anand P (2019) Chaotic grasshopper optimization algorithm for global optimization. Neural Comput & Applic 31:4385–4405. https://doi.org/10.1007/s00521-018-3343-2

2. Behera SK, Ghosh CN, Mishra DP et al (2020) Strength development and microstructural investigation of lead-zinc mill tailings based paste backfill with fly ash as alternative binder. Cement Concr Compos 109:103553. https://doi.org/10.1016/j.cemconcomp.2020.103553

3. Bhattacharya S (2021) Central composite design for response surface methodology and its application in pharmacy. In: Kayaroganam P (ed) Response Surface Methodology in Engineering Science. IntechOpen. https://doi.org/10.5772/intechopen.95835

4. Bouchehed A, Laouacheria F, Heddam S, Djemili L (2023) Machine learning for better prediction of seepage flow through embankment dams: Gaussian process regression versus SVR and RVM. Environ Sci Pollut Res 30:24751–24763. https://doi.org/10.1007/s11356-023-25446-2

5. Braik M, Hammouri A, Atwan J et al (2022) White Shark Optimizer: a novel bio-inspired meta-heuristic algorithm for global optimization problems. Knowl-Based Syst 243:108457. https://doi.org/10.1016/j.knosys.2022.108457

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