Artificial Neural Network for Predicting Global Sub-Daily Tropospheric Wet Delay

Mohammed, Jareer

Description

These are the full results from "Artificial Neural Network for Predicting global sub-daily Tropospheric Wet Delay" for the selected 505 stations. They are divided into: 1- Raw time series of the 505 stations for (ZWD, Pressure, Temperature and Integrated Water Vapour). 2- The R values between the actual and the predicted ZWD. 3- The Predicted and actual ZWD. 4- The difference between the actual and predicted ZWD. 5- the inputs files for the ANN processing (the time series in dat format).

Citations (0)

Mentions (0)

Metrics

Dataset Index

0.4

FAIR Score

65%

Citations

0

Mentions

0

Metrics Over Time

Publication Details

DOI

Publisher

Mendeley

License

Creative Commons Attribution 4.0 International

Assigned Domain

Subfield

Artificial Intelligence

Field

Computer Science

Domain

Physical Sciences

Confidence Score

43%

Source

Scholar Data Model

Keywords

Artificial Neural NetworksTropospheric Propagation Delays

Normalization Factors

FT

57.69

CTw

1.00

MTw

1.00