Weather forecasting using Deep Learning

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2022.

書目詳細資料
Main Authors:	Fahad, Sheikh Abdul, Trina Akand, Takowa Islam, Ahammed Raju, Md. Reaj Uddin, Yadav, Ranjita
其他作者:	Ahmed, Tanvir
格式:	Thesis
語言:	English
出版:	Brac University 2023
主題:	Deep learning Weather forecasting Linear regression Auto encoder Prediction de-noise Linear regression analysis Machine learning. Machine learning > Statistical methods > Congresses.
在線閱讀:	http://hdl.handle.net/10361/18149

id	10361-18149
record_format	dspace
spelling	10361-181492023-04-13T21:01:44Z Weather forecasting using Deep Learning Fahad, Sheikh Abdul Trina Akand, Takowa Islam Ahammed Raju, Md. Reaj Uddin Yadav, Ranjita Ahmed, Tanvir Department of Computer Science and Engineering, Brac University Deep learning Weather forecasting Linear regression Auto encoder Prediction de-noise Linear regression analysis Machine learning. Machine learning--Statistical methods--Congresses. This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2022. Cataloged from PDF version of thesis. Includes bibliographical references (pages 38-40). Global human life is significantly impacted by weather forecasts. It takes a lot of computing resources to solve mathematical equations that are based on climatic circumstances. As a result, during the past ten years, deep learning algorithms have been integrated with enormous amounts of weather observation data. At the moment, a lot of data is being consumed. So, we can increase the accuracy of weather forecasts by combining this enormous amount of data with deep learning methods. In this paper, we implement benchmark datasets for autoencoder and linear regression. We are using z500 dataset, temp 2m dataset and t850 data set. As training the linear regression on the full data will take a lot of memory which is why we took every 5th time step that almost give the same result. Using a linear regression approach and an auto encoder model, we trained and obtained day-level predictions using the ERA5 reanalysis dataset (Hersbach et al., 2020) to determine the accuracy of the test data and training data. Sheikh Abdul Fahad Takowa Islam Trina Akand Md. Reaj Uddin Ahammed Raju Ranjita Yadav B. Computer Science 2023-04-13T08:35:19Z 2023-04-13T08:35:19Z 2022 2022-09 Thesis ID: 18101462 ID: 17101333 ID: 17101385 ID: 18201202 http://hdl.handle.net/10361/18149 en Brac University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. 40 pages application/pdf Brac University
institution	Brac University
collection	Institutional Repository
language	English
topic	Deep learning Weather forecasting Linear regression Auto encoder Prediction de-noise Linear regression analysis Machine learning. Machine learning--Statistical methods--Congresses.
spellingShingle	Deep learning Weather forecasting Linear regression Auto encoder Prediction de-noise Linear regression analysis Machine learning. Machine learning--Statistical methods--Congresses. Fahad, Sheikh Abdul Trina Akand, Takowa Islam Ahammed Raju, Md. Reaj Uddin Yadav, Ranjita Weather forecasting using Deep Learning
description	This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2022.
author2	Ahmed, Tanvir
author_facet	Ahmed, Tanvir Fahad, Sheikh Abdul Trina Akand, Takowa Islam Ahammed Raju, Md. Reaj Uddin Yadav, Ranjita
format	Thesis
author	Fahad, Sheikh Abdul Trina Akand, Takowa Islam Ahammed Raju, Md. Reaj Uddin Yadav, Ranjita
author_sort	Fahad, Sheikh Abdul
title	Weather forecasting using Deep Learning
title_short	Weather forecasting using Deep Learning
title_full	Weather forecasting using Deep Learning
title_fullStr	Weather forecasting using Deep Learning
title_full_unstemmed	Weather forecasting using Deep Learning
title_sort	weather forecasting using deep learning
publisher	Brac University
publishDate	2023
url	http://hdl.handle.net/10361/18149
work_keys_str_mv	AT fahadsheikhabdul weatherforecastingusingdeeplearning AT trinaakandtakowaislam weatherforecastingusingdeeplearning AT ahammedrajumdreajuddin weatherforecastingusingdeeplearning AT yadavranjita weatherforecastingusingdeeplearning
_version_	1814308392708079616

Weather forecasting using Deep Learning

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