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Machine learning-based in-situ detection of toxic petroleum hydrocarbons in groundwater
Journal of Contaminant Hydrology,
2026
DOI:10.1016/j.jconhyd.2025.104771
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[2]
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Assessing the Interaction Between Geologically Sourced Hydrocarbons and Thermal–Mineral Groundwater: An Overview of Methodologies
Water,
2025
DOI:10.3390/w17131940
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[3]
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A Review of Subsidence Monitoring Techniques in Offshore Environments
Sensors,
2024
DOI:10.3390/s24134164
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[4]
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Anomaly detection in groundwater monitoring data using LSTM-Autoencoder neural networks
Environmental Monitoring and Assessment,
2024
DOI:10.1007/s10661-024-12848-z
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[5]
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Towards a smart water city: A comprehensive review of applications, data requirements, and communication technologies for integrated management
Sustainable Cities and Society,
2022
DOI:10.1016/j.scs.2021.103442
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[6]
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Fixed or mixed?
Farmer‐level
heterogeneity in response to changes in salinity
American Journal of Agricultural Economics,
2022
DOI:10.1111/ajae.12270
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[7]
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An assessment of probabilistic disaster in the oil and gas supply chain leveraging Bayesian belief network
International Journal of Production Economics,
2021
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[8]
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Machine learning and transport simulations for groundwater anomaly detection
Journal of Computational and Applied Mathematics,
2020
DOI:10.1016/j.cam.2020.112982
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[9]
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Quantitative decision making for a groundwater monitoring and subsurface contamination early warning network
Science of The Total Environment,
2019
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