DOI: 10.1016/s1452-3981(23)06701-9. Prediction of Zeta Potential of Decomposed Peat via Machine Learning: Comparative Study of Support Vector Machine and Artificial Neural Networks

Prediction of Zeta Potential of Decomposed Peat via Machine Learning: Comparative Study of Support Vector Machine and Artificial Neural Networks

10.1016/s1452-3981(23)06701-9

Crossref journal-article

Elsevier BV

International Journal of Electrochemical Science (78)

Bibliography

Li, H., Chen, F., Cheng, K., Zhao, Z., & Yang, D. (2015). Prediction of Zeta Potential of Decomposed Peat via Machine Learning: Comparative Study of Support Vector Machine and Artificial Neural Networks. International Journal of Electrochemical Science, 10(8), 6044â6056.

Authors 5

Hao Li (first)
Fudi Chen (additional)
Kewei Cheng (additional)
Zheze Zhao (additional)
Dazuo Yang (additional)

References 38 Referenced 15

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Dates

Type	When
Created	2 years, 1 month ago (June 26, 2023, 1:12 p.m.)
Deposited	11 months, 2 weeks ago (Sept. 2, 2024, 11:12 a.m.)
Indexed	6 months ago (Feb. 21, 2025, 5:30 p.m.)
Issued	10 years ago (Aug. 1, 2015)
Published	10 years ago (Aug. 1, 2015)
Published Print	10 years ago (Aug. 1, 2015)

Funders 2

National Aerospace Science Foundation of China 10.13039/501100010012
Region: Asia
pri (Trusts, charities, foundations (both public and private))
Labels1
1. China National Aerospace Science Foundation
Awards2
1. 19-3YJ09
2. 30901107
Zhejiang Province Public Welfare Technology Application Research Project 10.13039/501100010248
Region: Asia
pri (Other non-profit organizations)
Labels1
1. Public Welfare Technology Application Research Project of Zhejiang Province
Awards2
1. 201305043
2. 201305002

BibTeX

@article{Li_2015, title={Prediction of Zeta Potential of Decomposed Peat via Machine Learning: Comparative Study of Support Vector Machine and Artificial Neural Networks}, volume={10}, ISSN={1452-3981}, url={http://dx.doi.org/10.1016/s1452-3981(23)06701-9}, DOI={10.1016/s1452-3981(23)06701-9}, number={8}, journal={International Journal of Electrochemical Science}, publisher={Elsevier BV}, author={Li, Hao and Chen, Fudi and Cheng, Kewei and Zhao, Zheze and Yang, Dazuo}, year={2015}, month=aug, pages={6044–6056} }

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