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The Application of Machine Learning: Controlling the Preparation of Environmental Materials and Carbon Neutrality

Author

Listed:
  • Zhenxing Wang

    (South China Institute of Environmental Sciences, Ministry of Ecology and Environment of the People’s Republic of China, Guangzhou 510655, China)

  • Yunjun Yu

    (South China Institute of Environmental Sciences, Ministry of Ecology and Environment of the People’s Republic of China, Guangzhou 510655, China)

  • Kallol Roy

    (Institute of Computer Science, Faculty of Science and Technology, University of Tartu, 51009 Tartu, Estonia)

  • Cheng Gao

    (College of Hydrology and Water Resources, Hohai University, Nanjing 210098, China)

  • Lei Huang

    (School of Environmental Science and Engineering, Guangzhou University, Guangzhou 510006, China)

Abstract

The greenhouse effect is a severe global problem [...]

Suggested Citation

  • Zhenxing Wang & Yunjun Yu & Kallol Roy & Cheng Gao & Lei Huang, 2023. "The Application of Machine Learning: Controlling the Preparation of Environmental Materials and Carbon Neutrality," IJERPH, MDPI, vol. 20(3), pages 1-4, January.
    • Handle: RePEc:gam:jijerp:v:20:y:2023:i:3:p:1871-:d:1041332
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    References listed on IDEAS

    as
    1. Shiyang Liu & Xuefu Zhang, 2022. "Fault Diagnosis and Maintenance Countermeasures of Transverse Drainage Pipe in Subway Tunnel Based on Fault Tree Analysis," IJERPH, MDPI, vol. 19(23), pages 1-24, November.
    2. Smriti Mallapaty, 2020. "How China could be carbon neutral by mid-century," Nature, Nature, vol. 586(7830), pages 482-483, October.
    3. Benjamin J. Shields & Jason Stevens & Jun Li & Marvin Parasram & Farhan Damani & Jesus I. Martinez Alvarado & Jacob M. Janey & Ryan P. Adams & Abigail G. Doyle, 2021. "Bayesian reaction optimization as a tool for chemical synthesis," Nature, Nature, vol. 590(7844), pages 89-96, February.
    4. Chenrui Lu & Bing Wang & Tinggui Chen & Jianjun Yang, 2022. "A Document Analysis of Peak Carbon Emissions and Carbon Neutrality Policies Based on a PMC Index Model in China," IJERPH, MDPI, vol. 19(15), pages 1-16, July.
    5. Paul Raccuglia & Katherine C. Elbert & Philip D. F. Adler & Casey Falk & Malia B. Wenny & Aurelio Mollo & Matthias Zeller & Sorelle A. Friedler & Joshua Schrier & Alexander J. Norquist, 2016. "Machine-learning-assisted materials discovery using failed experiments," Nature, Nature, vol. 533(7601), pages 73-76, May.
    6. Xianqi Zhang & Zhiwen Zheng, 2022. "A Novel Groundwater Burial Depth Prediction Model Based on Two-Stage Modal Decomposition and Deep Learning," IJERPH, MDPI, vol. 20(1), pages 1-15, December.
    7. Tattini, Jacopo & Gargiulo, Maurizio & Karlsson, Kenneth, 2018. "Reaching carbon neutral transport sector in Denmark – Evidence from the incorporation of modal shift into the TIMES energy system modeling framework," Energy Policy, Elsevier, vol. 113(C), pages 571-583.
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    Cited by:

    1. Atef El Jery & Houman Kosarirad & Nedasadat Taheri & Maryam Bagheri & Moutaz Aldrdery & Abubakr Elkhaleefa & Chongqing Wang & Saad Sh. Sammen, 2023. "An Application of Ultrasonic Waves in the Pretreatment of Biological Sludge in Urban Sewage and Proposing an Artificial Neural Network Predictive Model of Concentration," Sustainability, MDPI, vol. 15(17), pages 1-16, August.

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