A machine learning approach to analyze and predict rainfall in different regions of Bangladesh
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2021.
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Brac University
2021
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| Online Access: | http://hdl.handle.net/10361/15196 |
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10361-151962022-01-26T10:10:23Z A machine learning approach to analyze and predict rainfall in different regions of Bangladesh Rahee, Arnob Nafiz, Md. Montasir Bhuiyan, Sania Azhmee Alam, Md. Ashraful Alam, Md. Golam Rabiul Department of Computer Science and Engineering, Brac University Rainfall Analysis Machine Learning Rainfall in Bangladesh Regression K-Nearest Neighbour Random Forest Decision Tree Machine Learning This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2021. Cataloged from PDF version of thesis. Includes bibliographical references (page 55-56). Rainfall has always been important in context of Bangladesh as almost 43% of the population depends on agriculture for their livelihood. Global warming has been taking a toll on environment and rainfall patterns have been changing around the world. Almost half the population depends on rainfall for irrigating their lands and grow crops. If rainfall can be predicted precisely then people involved with agricultural sector will be benefited. In this research, we analyzed the rainfall statistics on the basis of Bangladesh Meteorological Department’s data of rainfall of last 66 years. With Mann-Kendall Trend Test with 5% level of significance we tested the trend of 6 divisional stations of Bangladesh. Later we utilized three regression models to predict rainfall on basis of data from 1948 to 2014. We have also implemented those 3 regression models on 6 regional station data to understand if there is any change in accuracy. Trend tests showed no significant change in rainfall patterns in last 30 years. We also broke down the data to understand the hydrological regions of Bangladesh and the rainfall by stations. Arnob Rahee Md. Montasir Nafiz Sania Azhmee Bhuiyan B. Computer Science 2021-10-10T08:34:03Z 2021-10-10T08:34:03Z 2021 2021-08 Thesis ID 18101225 ID 17109028 ID 18101486 http://hdl.handle.net/10361/15196 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. 56 pages application/pdf Brac University |
| institution |
Brac University |
| collection |
Institutional Repository |
| language |
English |
| topic |
Rainfall Analysis Machine Learning Rainfall in Bangladesh Regression K-Nearest Neighbour Random Forest Decision Tree Machine Learning |
| spellingShingle |
Rainfall Analysis Machine Learning Rainfall in Bangladesh Regression K-Nearest Neighbour Random Forest Decision Tree Machine Learning Rahee, Arnob Nafiz, Md. Montasir Bhuiyan, Sania Azhmee A machine learning approach to analyze and predict rainfall in different regions of Bangladesh |
| description |
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2021. |
| author2 |
Alam, Md. Ashraful |
| author_facet |
Alam, Md. Ashraful Rahee, Arnob Nafiz, Md. Montasir Bhuiyan, Sania Azhmee |
| format |
Thesis |
| author |
Rahee, Arnob Nafiz, Md. Montasir Bhuiyan, Sania Azhmee |
| author_sort |
Rahee, Arnob |
| title |
A machine learning approach to analyze and predict rainfall in different regions of Bangladesh |
| title_short |
A machine learning approach to analyze and predict rainfall in different regions of Bangladesh |
| title_full |
A machine learning approach to analyze and predict rainfall in different regions of Bangladesh |
| title_fullStr |
A machine learning approach to analyze and predict rainfall in different regions of Bangladesh |
| title_full_unstemmed |
A machine learning approach to analyze and predict rainfall in different regions of Bangladesh |
| title_sort |
machine learning approach to analyze and predict rainfall in different regions of bangladesh |
| publisher |
Brac University |
| publishDate |
2021 |
| url |
http://hdl.handle.net/10361/15196 |
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