Title :
Forecasting of rainfall using ANN, GPS and mteorological data
Author :
Sachan, Abhishek
Author_Institution :
Comput. Sci. & Eng. Dept., Shri Ramswaroop Memorial Univ., Lucknow, India
Abstract :
Forecasting of rainfall and its variability is important for many real life applications such as hydrological cycle. Further, timely rainfall prediction for subcontinent countries is economically important because they have agro-based economy. Moreover, rainfall play huge role for many natural disasters such as landslide, flush flood etc. However, accurate prediction of rainfall in terms of timing and magnitude is still remains complex because it depends upon many parameters like water vapor, pressure, temperature, wind velocity etc. In this paper we have proposed an intelligent system to predict the rainfall for Bangalore region.
Keywords :
Global Positioning System; disasters; geophysics computing; radial basis function networks; rain; weather forecasting; wind; ANN; Bangalore region; GPS; Global Positioning System; agro-based economy; artificial neural network; hydrological cycle; intelligent system; mteorological data; natural disasters; pressure parameter; radial basis function networks; rainfall forecasting; subcontinent countries; temperature parameter; water vapor parameter; wind velocity parameter; Artificial neural networks; Delays; Global Positioning System; Neurons; Rain; Training; Water; Artificial Neural Network (ANN); Bernese software; Global Positioning System (GPS); Precipitable Water Vapor (PWV); Radial Basis Function (RBF); Troposphere; Zenith Wet Delay (ZWD);
Conference_Titel :
Convergence of Technology (I2CT), 2014 International Conference for
Print_ISBN :
978-1-4799-3758-5
DOI :
10.1109/I2CT.2014.7092314