Open AccessResult and Performance Analysis of Rainfall Prediction System Based on Deep Neural Network
Author(s) -
Akshay R. Naik,
A. V. Deorankar,
Premchand Ambhore
Publication year - 2020
Publication title -
international journal of scientific research in computer science, engineering and information technology
Language(s) - English
Resource type - Journals
ISSN - 2456-3307
DOI - 10.32628/cseit2063165
Subject(s) - artificial neural network , artificial intelligence , machine learning , random forest , computer science , decision tree , support vector machine , deep learning , ensemble learning , factory (object oriented programming) , modal , deep neural networks , chemistry , polymer chemistry , programming language
Rainfall prediction is useful for all people for decision making in all fields, such as out door gamming, farming, traveling, and factory and for other activities. We studied various methods for rainfall prediction such as machine learning and neural networks. There is various machine learning algorithms are used in previous existing methods such as naïve byes, support vector machines, random forest, decision trees, and ensemble learning methods. We used deep neural network for rainfall prediction, and for optimization of deep neural network Adam optimizer is used for setting modal parameters, as a result our method gives better results as compare to other machine learning methods.