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Found 4785 dataset(s) matching "Predictive models".
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Multiple modeling frameworks were used to predict daily temperatures at 0.5m depth intervals for a set of diverse lakes in the U.S. states of Minnesota and Wisconsin. Process-Based (PB) models...
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Multiple modeling frameworks were used to predict daily temperatures at 0.5m depth intervals for a set of diverse lakes in the U.S. states of Minnesota and Wisconsin. Process-Based (PB) models...
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Multiple modeling frameworks were used to predict daily temperatures at 0.5m depth intervals for a set of diverse lakes in the U.S. states of Minnesota and Wisconsin. Process-Based (PB) models...
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Multiple modeling frameworks were used to predict daily temperatures at 0.5m depth intervals for a set of diverse lakes in the U.S. states of Minnesota and Wisconsin. General Lake Model verion 2...
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This data release contains model inputs, R code, and model outputs for predicting depth to bedrock in the Delaware River Basin at a 1km gridded resolution with a random forest model. Model inputs...
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This metadata record describes outputs from 12 configurations of long short-term memory (LSTM) models which were used to predict streamflow drought occurrence at 384 stream gage locations in the...
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<p>Several models were used to improve water temperature prediction in the Delaware River Basin. <p>PRMS-SNTemp was used to predict daily temperatures at 456 stream reaches in the...
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This data release contains the forcings and outputs of 7-day ahead maximum water temperature forecasting models that makes predictions at 70 river reaches in the upper Delaware River Basin. This...
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This paper compares the relative predictive ability and applicability to NTA workflows of three RT prediction models: (1) a logP (octanol-water partition coefficient)-based model using EPI SuiteTM...
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Studies utilizing Global Positioning System (GPS) telemetry rarely result in 100% fix success rates (FSR). Many assessments of wildlife resource use do not account for missing data, either...
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This dataset is a collection and inventory of existing seafloor mapping, ground-truthing, and predictive habitat modeling data within the Gulf of Mexico. The inventory was compiled by the...
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Results from generalized additive models (GAM), random forest models (RFM), and cubist models (CUB) for three Dauphin Island Sealab (DIS) operated salinity sites in Mobile Bay are reported in this...
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COMBINE_CONC_A0_2016_without_DMS_AVG.tar – annual average model predicted concentrations without DMS chemistry COMBINE_CONC_A_2016_annual_AVG.tar – annual average model predicted concentrations...
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This data release includes 5 files containing model inputs and resulting model predictions. A previously-calibrated spatially referenced regression (SPARROW) model was used to estimate effects of...
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<p>This data release item contains water temperature predictions for 455 river sites across the U.S. Predictions are from the models described by Rahmani et al. (2021b).</p>
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A random forest regression (RFR) model was developed to predict groundwater fluoride concentrations in four western United Stated principal aquifers —California Coastal basin-fill aquifers,...
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<p>This data release provides the predictions from stream temperature models described in Chen et al. 2021. Briefly, various deep learning and process-guided deep learning models were built...
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Globally, groundwater dependent ecosystems (GDEs) are increasingly vulnerable to groundwater extraction and land use practices. Groundwater supports these ecosystems by providing inflow, which can...
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Multiple modeling frameworks were used to predict daily temperatures at 0.5m depth intervals for a set of diverse lakes in the U.S. state of Minnesota. Uncalibrated models used default...
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<p>This data release component contains water temperature predictions in 118 river catchments across the U.S. Predictions are from the four models described by Rahmani et al. (2020):...
