Computer Science
Scientific paper
Jun 2011
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2011adspr..47.1949d&link_type=abstract
Advances in Space Research, Volume 47, Issue 11, p. 1949-1957.
Computer Science
Scientific paper
By using a Doppler Weather Radar (DWR) at Shriharikota (13.66°N & 80.23°E), an Artificial Neural Network (ANN) based technique is proposed to improve the accuracy of rain intensity estimation. Three spectral moments of a Doppler spectra are utilized as an input data to an ANN. Rain intensity, as measured by the tipping bucket rain gauges around the DWR station, are considered as a target values for the given inputs. Rain intensity as estimated by the developed ANN model is validated by the rain gauges measurements. With the help of a developed technique, reasonable improvement in the estimation of rain intensity is observed. By using the developed technique, root mean square error and bias are reduced in the range of 34-18% and 17-3% respectively, compared to Z-R approach.
Das Jayajit
Dutta Devajyoti
Gairola R. M.
Kannan A. M. B.
Sen G. K.
No associations
LandOfFree
An Artificial Neural Network based approach for estimation of rain intensity from spectral moments of a Doppler Weather Radar does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.
If you have personal experience with An Artificial Neural Network based approach for estimation of rain intensity from spectral moments of a Doppler Weather Radar, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and An Artificial Neural Network based approach for estimation of rain intensity from spectral moments of a Doppler Weather Radar will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-980216