Estimation of location-specific precipitation using Deep Neural Networks

arXiv (Cornell University) 2026 Preprint Open access

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Authors: Bipin Kumar, Bhvisy Kumar Yadav, Bhupendra Bahadur Singh, R. Chattopadhyay
DOI: 10.5281/zenodo.18516054
Cited by: 0

Abstract

These two codes are associated with the study “Estimation of Location-Specific Precipitation Using Deep Neural Networks.” The script 10p_training_code.py is used to train the neural network model using the 10 nearest grid points as input features, while cal_mae_rmse.py is used to evaluate the trained model on unseen data by computing performance metrics such as MAE and RMSE.

Fields of Study & Subjects

Precipitation Measurement and Analysis Hydrological Forecasting Using AI Meteorological Phenomena and Simulations

Publication details

Journal / source
arXiv (Cornell University)
Publication date
7 February 2026
Language
EN
Document type
Preprint