Convergence of Real-Time Analytical Framework with E-Waste Disposal Using Machine Learning-Centered Hybrid Neural Networks-Reference-Cited by-同舟云学术

Convergence of Real-Time Analytical Framework with E-Waste Disposal Using Machine Learning-Centered Hybrid Neural Networks

Published:2023-01-30 Issue: Volume: Page:
ISSN:2250-0545
Container-title:Journal of The Institution of Engineers (India): Series C
language:en
Short-container-title:J. Inst. Eng. India Ser. C

Author:

Raghavendra T. S.,Nagaraja S. R.,Mohan K. G.

Publisher

Springer Science and Business Media LLC

Subject

Industrial and Manufacturing Engineering,Mechanical Engineering,Ocean Engineering,Aerospace Engineering

Link

https://link.springer.com/content/pdf/10.1007/s40032-023-00912-5.pdf

Reference23 articles.

1. R. Widmer et al., Global perspectives on E-waste. Environ. Impact Assess. Rev. 25, 436–458 (2005)

2. I. Dalrymple, N. Wright, R. Kellner, N. Bains, K. Geraghty, M. Goosey, L. Lightfoot, C-Tech Innovation Ltd., PK Kellner Environment, Rohm & Hass Electronic Materials Ltd, An integrated approach to electronic waste (WEEE) recycling. Circuit World 33, 52 (2006)

3. B. Ádám, T. Göen, P.T. Scheepers, D. Adliene, B. Batinic, L.T. Budnik, R.C. Duca, M. Ghosh, D.I. Giurgiu, L. Godderis, O. Goksel, From inequitable to sustainable e-waste processing for reduction of impact on human health and the environment. Environ. Res. 194, 110728 (2021). https://doi.org/10.1016/j.envres.2021.110728

4. Encyclopedia Britannica. Electronic Waste. Encyclopaedia Britannica Inc., published 26 May 2016. https://www.britannica.com/technology/electronic-waste, Accessed 02 Sept 2020.

5. C.P. Baldé, R. Kuehr, K. Blumenthal, S. Fondeur Gill, M. Kern, P. Micheli, E. Magpantay, J. Huisman E-waste Statistics: Guidelines on Classification, Reporting and Indicators United Nations University, IAS - SCYCLE, Bonn, Germany (2015)