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Found 52 dataset(s) matching "Machine Learning (ML) Models".
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We applied machine learning (ML) models to forecast streamflow drought from 1 to 13 weeks into the future at more than 3,000 streamgage locations across the Conterminous United States. We applied...
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ml_uncertainty: A Python module for estimating uncertainty in predictions of machine learning models
This software is a Python module for estimating uncertainty in predictions of machine learning models. It is a Python package that calculates uncertainties in machine learning models using...
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Salinity dynamics in the Delaware Bay estuary are a critical water quality concern as elevated salinity can damage infrastructure and threaten drinking water supplies. Current state-of-the-art...
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A series of machine learning (ML) models were developed for Minnesota. The ML models were trained and tested using suspended sediment, bedload, streamflow, and geospatial data to predicted...
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This report presents the far-field stress predictions at two locations along the vertical section of Utah FORGE Well 16A (78)-32 using a physics-based thermo-poro-mechanical model. Three principal...
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This is the geospatial and hydroclimate input data used to develop data-driven Machine Learning (ML) models as well as model estimated water quality based risk metrics and watershed health...
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Enhanced geothermal systems (EGS) can provide a sustainable and renewable solution to the new energy transition. Its potential relies on the ability to create a reservoir and to accurately...
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Due to the increasing diversity of organic contaminants discharged into anoxic water environments, reactivity prediction is necessary for chemical persistence evaluation for water treatment and...
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Groundwater is a vital resource in the Mississippi embayment of the central United States. An innovative approach using machine learning (ML) was employed to predict groundwater salinity—including...
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Groundwater is a vital resource in the Mississippi embayment of the central United States. An innovative approach using machine learning (ML) was employed to predict groundwater salinity—including...
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Groundwater is a vital resource in the Mississippi embayment of the central United States. An innovative approach using machine learning (ML) was employed to predict groundwater salinity—including...
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Groundwater is a vital resource in the Mississippi embayment of the central United States. An innovative approach using machine learning (ML) was employed to predict groundwater salinity—including...
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Autonomous recording units are increasingly being used to monitor wildlife on large geographic and temporal scales, paired with machine learning (ML) to automate detection of wildlife. However,...
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Geothermal power plants typically show decreasing heat and power production rates over time. Mitigation strategies include optimizing the management of existing wells - increasing or decreasing...
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This dataset contains a comparison of packet loss counts vs handovers using four different methods: baseline, heuristic, distance, and machine learning, as well as the data used to train a machine...
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Subsurface data analysis, reservoir modeling, and machine learning (ML) techniques have been applied to the Brady Hot Springs (BHS) geothermal field in Nevada, USA to further characterize the...
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This report reviews the training of machine learning algorithms to laboratory triaxial ultrasonic velocity data for Utah FORGE Well 16A(78)-32. Three machine learning (ML) predictive models were...
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This task completion report documents the development and implementation of machine learning (ML) models for the prediction of in-situ vertical (Sv), minimum horizontal (SHmin) and maximum...
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The high performance computing (HPC) and big data (BD) communities traditionally have pursued independent trajectories in the world of computational science. HPC has been synonymous with modeling...
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In this paper, we present an analysis using unsupervised machine learning (ML) to identify the key geologic factors that contribute to the geothermal production in Brady geothermal field. Brady is...
