Deep insight: an efficient hybrid model for oil well production forecasting using spatio-temporal convolutional networks and Kolmogorov–Arnold networks
- DOI
- 10.1038/s41598-025-91412-2
- Published
- 2025-03-10
- Container
- Scientific Reports
- Publisher
- Springer Science and Business Media LLC
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1038/s41598-025-91412-2,
title = {Deep insight: an efficient hybrid model for oil well production forecasting using spatio-temporal convolutional networks and Kolmogorov–Arnold networks},
author = {Yandong Hu and Xiankang Xin and Gaoming Yu and Wu Deng},
year = {2025},
journal = {Scientific Reports},
doi = {10.1038/s41598-025-91412-2},
url = {https://doi.org/10.1038/s41598-025-91412-2}
}RIS
TY - JOUR TI - Deep insight: an efficient hybrid model for oil well production forecasting using spatio-temporal convolutional networks and Kolmogorov–Arnold networks AU - Yandong Hu AU - Xiankang Xin AU - Gaoming Yu AU - Wu Deng PY - 2025 JO - Scientific Reports DO - 10.1038/s41598-025-91412-2 UR - https://doi.org/10.1038/s41598-025-91412-2 ER -
APA
Hu, Y., Xin, X., Yu, G., & Deng, W. (2025). Deep insight: an efficient hybrid model for oil well production forecasting using spatio-temporal convolutional networks and Kolmogorov–Arnold networks. Scientific Reports. https://doi.org/10.1038/s41598-025-91412-2
Source records
- crossref · retrieved 2026-09-26T07:38:32.684Z