Open AccessUse of Appropriate Loss Function in Rainfall Prediction using Deep Learning
Author(s) -
Vivek Patel,
R.D. Morena
Publication year - 2020
Publication title -
international journal of engineering and advanced technology
Language(s) - English
Resource type - Journals
ISSN - 2249-8958
DOI - 10.35940/ijeat.d7515.089620
Subject(s) - artificial neural network , deep learning , cross entropy , artificial intelligence , entropy (arrow of time) , computer science , agriculture , binary classification , machine learning , meteorology , environmental science , geography , pattern recognition (psychology) , support vector machine , quantum mechanics , physics , archaeology
India is an agricultural country, and rainfall is the main source of irrigation for agriculture. Prediction of rainfall is very crucial for farmers to make decisions. In this research paper, the prediction model has been developed through deep learning using historical data of 10 years of rainfall. A deep learning approach used Keras API with an artificial neural network technique to predict the daily rainfall. The prediction model has been assessed by four-loss function, i.e., MSE, MAE, Hinge, and Binary Cross-Entropy.