Prediction and field application of water-conducting fracture zone height using a PSO-BP neural network optimised by dynamic mutation.
- DOI
- 10.1038/s41598-026-62376-8
- Published
- 2026 Jul 14
- Container
- Scientific reports
- Publisher
- Not recorded
- Open access
- no
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Cite this work
BibTeX
@article{allodium:10.1038/s41598-026-62376-8,
title = {Prediction and field application of water-conducting fracture zone height using a PSO-BP neural network optimised by dynamic mutation.},
author = {Guo W and Wang Y and Tan Y and Liu X and Feng Y and Wei S and Wang X and Lu W},
year = {2026},
journal = {Scientific reports},
doi = {10.1038/s41598-026-62376-8},
url = {https://doi.org/10.1038/s41598-026-62376-8}
}RIS
TY - JOUR TI - Prediction and field application of water-conducting fracture zone height using a PSO-BP neural network optimised by dynamic mutation. AU - Guo W AU - Wang Y AU - Tan Y AU - Liu X AU - Feng Y AU - Wei S AU - Wang X AU - Lu W PY - 2026 JO - Scientific reports DO - 10.1038/s41598-026-62376-8 UR - https://doi.org/10.1038/s41598-026-62376-8 ER -
APA
W, G., Y, W., Y, T., X, L., Y, F., S, W., X, W., & W, L. (2026). Prediction and field application of water-conducting fracture zone height using a PSO-BP neural network optimised by dynamic mutation.. Scientific reports. https://doi.org/10.1038/s41598-026-62376-8
Source records
- pubmed · retrieved 2026-09-25T15:00:10.750Z
- europe-pmc · retrieved 2026-09-25T15:00:10.720Z