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1,773
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1,773 results for “Predictive model”
Universal Rapid Weather Prediction Model (Sonagi Model) Forecast Result
Universal Rapid Weather Prediction Model (Sonagi Model) Forecast Result / 10 Days / Created By Jihyeon Yoon(somehowme@gmail.com, flyingtext@nate.com, flyingtext@hotmail.com) Latest prediction can be available on map at https://sonagi-weather.web.app Prediction is based on the observation data of - Korea Meteorological Administration API - United States National Weather Service API - Canada MSC GeoMet API
Universal Rapid Weather Prediction Model (Sonagi Model) Forecast Result
Universal Rapid Weather Prediction Model (Sonagi Model) Forecast Result / 15 Days / Created By Jihyeon Yoon(somehowme@gmail.com, flyingtext@nate.com, flyingtext@hotmail.com) Latest prediction can be available on map at https://sonagi-weather.web.app Prediction is based on the observation data of - Korea Meteorological Administration API - United States National Weather Service API - Canada MSC GeoMet API
Universal Rapid Weather Prediction Model (Sonagi Model) Forecast Result
Universal Rapid Weather Prediction Model (Sonagi Model) Forecast Result / 15 Days / Created By Jihyeon Yoon(somehowme@gmail.com, flyingtext@nate.com, flyingtext@hotmail.com) Latest prediction can be available on map at https://sonagi-weather.web.app Prediction is based on the observation data of - Korea Meteorological Administration API - United States National Weather Service API - Canada MSC GeoMet API
Universal Rapid Weather Prediction Model (Sonagi Model) Forecast Result
Universal Rapid Weather Prediction Model (Sonagi Model) Forecast Result / 15 Days / Created By Jihyeon Yoon(somehowme@gmail.com, flyingtext@nate.com, flyingtext@hotmail.com) Latest prediction can be available on map at https://sonagi-weather.web.app Prediction is based on the observation data of - Korea Meteorological Administration API - United States National Weather Service API - Canada MSC GeoMet API
Universal Rapid Weather Prediction Model (Sonagi Model) Forecast Result
Universal Rapid Weather Prediction Model (Sonagi Model) Forecast Result / 15 Days / Created By Jihyeon Yoon(somehowme@gmail.com, flyingtext@nate.com, flyingtext@hotmail.com) Latest prediction can be available on map at https://sonagi-weather.web.app Prediction is based on the observation data of - Korea Meteorological Administration API - United States National Weather Service API - Canada MSC GeoMet API
Universal Rapid Weather Prediction Model (Sonagi Model) Forecast Result
Universal Rapid Weather Prediction Model (Sonagi Model) Forecast Result / 15 Days / Created By Jihyeon Yoon(somehowme@gmail.com, flyingtext@nate.com, flyingtext@hotmail.com) Latest prediction can be available on map at https://sonagi-weather.web.app Prediction is based on the observation data of - Korea Meteorological Administration API - United States National Weather Service API - Canada MSC GeoMet API
Universal Rapid Weather Prediction Model (Sonagi Model) Forecast Result
Universal Rapid Weather Prediction Model (Sonagi Model) Forecast Result / 15 Days / Created By Jihyeon Yoon(somehowme@gmail.com, flyingtext@nate.com, flyingtext@hotmail.com) Latest prediction can be available on map at https://sonagi-weather.web.app Prediction is based on the observation data of - Korea Meteorological Administration API - United States National Weather Service API - Canada MSC GeoMet API - ECMWF IFS04 within Europe area
InfoHiC models for cancer Hi-C prediction
<p>InfoHiC models for cancer Hi-C prediction</p>
InfoHiC models for cancer Hi-C prediction (T47D, 1Mb window, 40kb resolution)
<p>InfoHiC models for cancer Hi-C prediction</p> <ul> <li>T47D</li> <li>1Mb window</li> <li>40kb resolution</li> <li>CSCN encoding</li> </ul>
InfoHiC models for cancer Hi-C prediction (NPC, 1Mb window, 40kb resolution)
<div> <p>InfoHiC models for cancer Hi-C prediction</p> <ul> <li>NPC</li> <li>1Mb window</li> <li>40kb resolution</li> <li>CSCN decoding</li> </ul> </div>
InfoHiC models for cancer Hi-C prediction (K562, 1Mb window, 10kb resolution)
<p>InfoHiC models for cancer Hi-C prediction</p> <ul> <li>K562</li> <li>1Mb window</li> <li>10kb resolution</li> <li>CSCN encoding</li> </ul>
Post-Translational Modification Prediction via Prompt-Based Fine-Tuning of a GPT-2 Model
<p>Training and Benchmark datasets for 19 PTMGPT2 models</p>
Enhancing Streamflow Prediction through Multi-model Ensemble Framework and Machine Learning Techniques
<p>This file contains python code used in this study and data used to plot figures. </p>
Figures 1–5. Pseudococcus longispinus habitus and distribution. 1 in Predicting the potential distribution of Pseudococcus longispinus (Targioni-Tozzetti) (Hemiptera: Pseudococcidae) in South Korea using a CLIMEX model
Figures 1–5. Pseudococcus longispinus habitus and distribution. 1) Pseudococcus longispinus on Dracaena plant from the Philippines. 2–4) Simulated geographic distribution of P. longispinus in South Korea using CLIMEX model with meteorological data. 2) The 2020s. 3) The 2050s. 4) The 2090s. 5) Present global distribution of P. longispinus used in CLIMEX model.
Advanced neural network-based model for predicting court decisions on child custody
Open the record for dataset details and reuse information.
Advanced Iterative Model for Lumpy Skin Disease Prediction Using Fine-grained Feature Fusion and Adaptive Transfer Learning
Open the record for dataset details and reuse information.
Figure 1 in How can global climate change influence the geographic distribution of the eucalyptus yellow beetle? Modeling and prediction for Brazil
Figure 1. Current potential geographic distribution of Costalimaita ferruginea determined by the algorithm Envelope Score (AUC = 0.808). The numbers 1 to 5 represent the Brazilian biomes, being 1 = Amazônia, 2 = Caatinga, 3 = Cerrado, 4 = Pantanal, 5 = Mata Atlântica e 6 = Pampa.
An empirical model for predicting insects diapause termination and phenology: an application to Cydia pomonella
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Supplementary material 1 from: Capinha C, Essl F, Seebens H, Pereira HM, Kühn I (2018) Models of alien species richness show moderate predictive accuracy and poor transferability. NeoBiota 38: 77-96. https://doi.org/10.3897/neobiota.38.23518
Table A1–A5 :
A Predictive Model for the Streamwise Velocity in the Near-neutral Atmospheric Surface Layer
<p>A Predictive Model for the Streamwise Velocity in the Near-neutral Atmospheric Surface Layer</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.