Analysis of Precipitation Variability using Memory Based Artificial Neural Networks
Analysis of Precipitation Variability using Memory Based Artificial Neural Networks is a scholarly work, published in 2019 in ''International Journal of Applied Metaheuristic Computing''. The main subjects of the publication include climatology, electricity market, hydrological model, artificial neural network, downscaling, environmental science, mean squared error, precipitation, numerical weather prediction, and computer science. Results obtained by using 24 years of daily data sets show that GMNN-GA is efficient in downscaling daily precipitation series with maximum daily annual mean error of 6.78%.