Volume- 9
Issue- 4
Year- 2021
DOI: 10.21276/ijircst.2021.9.4.7 | DOI URL: https://doi.org/10.21276/ijircst.2021.9.4.7 Crossref
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0) (http://creativecommons.org/licenses/by/4.0)
Article Tools: Print the Abstract | Indexing metadata | How to cite item | Email this article | Post a Comment
N. Sri Lakshmi , P. Ajimunnisa, V. Lakshmi Prasanna, T. YugaSravani, M. RaviTeja
Weather forecasting has become important now a day because of varying climatic conditions around the world. Many technologies have been introduced to predict the weather whose accuracy is around 70%.Weather forecasting is used in machine learning. It is a powerful technique to predict the weather with more accuracy. Weather dataset is collected and analysed and algorithms on it to predict the weather. Using a Back Propagation Neural Network the error rate becomes less and many factors that are involved to predicting the weather gives the accurate results. To compare and evaluate the performance of above model and the programming was carried out using Visual Studio as a tool.
Assistant Professor, Department of Computer Science and Engineering, Dhanekula Institute of Engineering and Technology, Vijayawada, Andhra Pradesh, India (ajimunnisapathan1999@gmail.com)
No. of Downloads: 63 | No. of Views: 1189
Lingxi Xiao, Ruilin Xu, Yiru Cang, Yan Chen, Yijing Wei.
May 2024 - Vol 12, Issue 3
Anuj Kumar Kem, Ayush Chauhan, Mohan Agnihotri, Aniruddh Kumar.
May 2024 - Vol 12, Issue 3
Pravek Sharma, Dr. Rajesh Tyagi, Dr. Priyanka Dubey.
May 2024 - Vol 12, Issue 3