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Data · dataset · 2023

2DCNN Prediction of Shenzhen Surface ozone

Listed in ScienceDB

Description

This dataset includes the 2-D Convolutional neural network (2DCNN) predictions of Shenzhen driven by different sources of meteorological data.The description of files included in this dataset are listed below:train_x.npy: The Python Numpy array of data used to train the 2DCNN modeltest_x.npy: The Python Numpy array of data used as the test set the 2DCNN modelval_x.npy: The Python Numpy array of data used to independently validate the 2DCNN modely_pred_train.npy: The Python Numpy array of 2DCNN prediction of training set. y_pred_test.npy: The Python Numpy array of 2DCNN prediction of test set.y_pred_val.npy:  The Python Numpy array of 2DCNN prediction of independent validation set.info.npz: The compressed Python Numpy array of latitudes (lat), longitudes (lon), features(vardic) of the 2DCNN input data. 2DCNN-FNL2021.npz: The compressed Python Numpy array of in input (X), prediction (Y) and a list of dates for 2DCNN-FNL2021 simulation.2DCNN-FNL2019.npz: The compressed Python Numpy array of in input (X), prediction (Y) and a list of dates for 2DCNN-FNL2019 simulation.2DCNN-ERA5-2021.npz: The compressed Python Numpy array of in input (X), prediction (Y) and a list of dates for 2DCNN-ERA5-2021 simulation.2DCNN-ERA5-2019.npz: The compressed Python Numpy array of in input (X), prediction (Y) and a list of dates for 2DCNN-ERA5-2019 simulation.2DCNN-EDA-2021.npz: The compressed Python Numpy array of in input (X), prediction (Y) and a list of dates for 2DCNN-EDA-2021 simulation.2DCNN-EDA-2019.npz: The compressed Python Numpy array of in input (X), prediction (Y) and a list of dates for 2DCNN-EDA-2019 simulation.2DCNN-ESOF-2021-24hr.npz: The compressed Python Numpy array of in input (X), prediction (Y) and a list of dates for 2DCNN-ESOF-2021-24hr simulation.2DCNN-ESOF-2021-48hr.npz: The compressed Python Numpy array of in input (X), prediction (Y) and a list of dates for 2DCNN-ESOF-2021-48hr simulation.2DCNN-ESOF-2021-72hr.npz: The compressed Python Numpy array of in input (X), prediction (Y) and a list of dates for 2DCNN-ESOF-2021-72hr simulation.2DCNN-ESOF-2019-24hr.npz: The compressed Python Numpy array of in input (X), prediction (Y) and a list of dates for 2DCNN-ESOF-2019-24hr simulation.2DCNN-ESOF-2019-48hr.npz: The compressed Python Numpy array of in input (X), prediction (Y) and a list of dates for 2DCNN-ESOF-2019-48hr simulation.2DCNN-ESOF-2019-72hr.npz: The compressed Python Numpy array of in input (X), prediction (Y) and a list of dates for 2DCNN-ESOF-2019-72hr simulation.2DCNN-ESOF-2019.npz: The compressed Python Numpy array of in input (X), prediction (Y) and a list of dates for 2DCNN-ESOF-2019 216 hr forecast.

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Inferred from text
Simulation 75%
Provenance · 1 source records, 11 field assertions
SourceKeyLast seenRaw
ScienceDB10.57760/sciencedb.o00005.000259 d agoJSON v1
FieldAssertionExtractorEvidence
access_levelsource · scidb cnconnector:scidb_cn@1.0.0
concepts[field].local:field:earth-environmentalmapping · scidb cnconnector:scidb_cn@1.0.0
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concepts[field].local:field:humanitiesmapping · scidb cnconnector:scidb_cn@1.0.0
concepts[field].local:field:life-sciencesmapping · scidb cnconnector:scidb_cn@1.0.0
concepts[field].local:field:social-sciencemapping · scidb cnconnector:scidb_cn@1.0.0
concepts[method].local:method:simulationenrichment · scidb cnkeyword-concept-rules@1.0.0title+description (75%)
descriptionsource · scidb cnconnector:scidb_cn@1.0.0/metadata/dc/description
licensesource · scidb cnconnector:scidb_cn@1.0.0/metadata/dc/rights
publication_datesource · scidb cnconnector:scidb_cn@1.0.0
titlesource · scidb cnconnector:scidb_cn@1.0.0/metadata/dc/title