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.
Links
Where it is published
- DOI doi.org/10.57760/sciencedb.o00005.00025 ↗
DOI / persistent id · from scidb cn
Catalogue records · 1
- OAI-PMH record scidb.cn/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=10.57760%2… ↗
metadata API · from scidb cn
Topics
- From keywords
- Earth & Environmental Science · Engineering · Humanities · Life Sciences · Social Science
- Inferred from text
- Simulation 75%
Provenance · 1 source records, 11 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| ScienceDB | 10.57760/sciencedb.o00005.00025 | 9 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:earth-environmental | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:engineering | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:humanities | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:life-sciences | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:social-science | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[method].local:method:simulation | enrichment · scidb cn | keyword-concept-rules@1.0.0 | title+description (75%) |
| description | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/description |
| license | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/rights |
| publication_date | source · scidb cn | connector:scidb_cn@1.0.0 | |
| title | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/title |