Carbon peaking prediction scenarios based on different neural network models: A case study of Guizhou Province.

Lian D, Yang SQ, Yang W, Zhang M, Ran WR

DOI: 10.1371/journal.pone.0296596
Published: 2024
Container: PloS one
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.1371/journal.pone.0296596,
  title = {Carbon peaking prediction scenarios based on different neural network models: A case study of Guizhou Province.},
  author = {Lian D and Yang SQ and Yang W and Zhang M and Ran WR},
  year = {2024},
  journal = {PloS one},
  doi = {10.1371/journal.pone.0296596},
  url = {https://doi.org/10.1371/journal.pone.0296596}
}

RIS

TY  - JOUR
TI  - Carbon peaking prediction scenarios based on different neural network models: A case study of Guizhou Province.
AU  - Lian D
AU  - Yang SQ
AU  - Yang W
AU  - Zhang M
AU  - Ran WR
PY  - 2024
JO  - PloS one
DO  - 10.1371/journal.pone.0296596
UR  - https://doi.org/10.1371/journal.pone.0296596
ER  -

APA

D, L., SQ, Y., W, Y., M, Z., & WR, R. (2024). Carbon peaking prediction scenarios based on different neural network models: A case study of Guizhou Province.. PloS one. https://doi.org/10.1371/journal.pone.0296596

Source records

pubmed · retrieved 2026-09-27T13:07:04.804Z