Open Access
Digital twins of the natural environment
Publication type: Journal Article
Publication date: 2021-10-12
PubMed ID:
34693377
General Decision Sciences
Abstract
Digital twins emerged in the field of engineering but are now being applied in many areas of study. This article reflects on the enormous potential of digital twins of the natural environment and proposes an approach that builds on the massive legacy of process model understanding in this area combined with new insights from data understanding, including from AI/machine learning.
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Metrics
57
Total citations:
57
Citations from 2024:
37
(64.91%)
Cite this
GOST |
RIS |
BibTex |
MLA
Cite this
RIS
Copy
TY - JOUR
DO - 10.1016/j.patter.2021.100359
UR - https://doi.org/10.1016/j.patter.2021.100359
TI - Digital twins of the natural environment
T2 - Patterns
AU - Blair, Gordon S.
PY - 2021
DA - 2021/10/12
PB - Elsevier
SP - 100359
IS - 10
VL - 2
PMID - 34693377
SN - 2666-3899
ER -
Cite this
BibTex (up to 50 authors)
Copy
@article{2021_Blair,
author = {Gordon S. Blair},
title = {Digital twins of the natural environment},
journal = {Patterns},
year = {2021},
volume = {2},
publisher = {Elsevier},
month = {oct},
url = {https://doi.org/10.1016/j.patter.2021.100359},
number = {10},
pages = {100359},
doi = {10.1016/j.patter.2021.100359}
}
Cite this
MLA
Copy
Blair, Gordon S.. “Digital twins of the natural environment.” Patterns, vol. 2, no. 10, Oct. 2021, p. 100359. https://doi.org/10.1016/j.patter.2021.100359.