Prediction of rainfall using data mining techniques
This thesis report is submitted in partial fulfilment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2017.
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BRAC University
2018
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| Онлайн доступ: | http://hdl.handle.net/10361/9489 |
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10361-94892022-01-26T10:10:25Z Prediction of rainfall using data mining techniques Prema, Fahmida Tasnim Ahmed, Sharmin Islam, Md. Rifat Tairin, Suraiya Islam, Md. Saiful Department of Computer Science and Engineering, BRAC University Rainfall Data mining Climatic indices This thesis report is submitted in partial fulfilment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2017. Cataloged from PDF version of thesis report. Includes bibliographical references (pages 36-37). The research for this paper concentrates on finding inter-relations between various climatic indices and predict precipitation consequently. And since rainfall is the prominent reason behind flood, our study can aid immensely in predicting flood and designing a proper risk management system. Flood has been a major hindrance in the path of development for Bangladesh. Being a riverine country, flood occurs in Bangladesh almost every other year. Predicting flood accurately can help us in developing our economy. Our study shows how the climatic parameters (SOI,El Nino) are responsible for major rainfall in Bangladesh. Though many other researches on predicting rainfall have been conducted using other climatic factors, the southern oscillation index and the El nino 3.4 show stronger correlation with rainfall in our country than the others. For establishing a relationship among rainfall ,SOI and El Nino , we have applied Data Mining technique. The specific data mining algorithms that we have implemented in our paper are K-clustering, Decision tree and Regression model. The outputs of these algorithms give us a straightforward relationship between rainfall and the input parameters. Implementing our method on the dataset of rainfall for the past couple of years, our estimated rainfall is almost the same as the actual ones of those years. So in designing a feasible rainfall prediction model for Bangladesh, our work can play a significant role due to its high efficiency. Fahmida Tasnim Prema Sharmin Ahmed Md. Rifat Islam B. Computer Science and Engineering 2018-02-18T03:51:50Z 2018-02-18T03:51:50Z 2017 2017 Thesis ID 12201069 ID 17141001 ID 13110015 http://hdl.handle.net/10361/9489 en BRAC University thesis reports 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. 38 pages application/pdf BRAC University |
| institution |
Brac University |
| collection |
Institutional Repository |
| language |
English |
| topic |
Rainfall Data mining Climatic indices |
| spellingShingle |
Rainfall Data mining Climatic indices Prema, Fahmida Tasnim Ahmed, Sharmin Islam, Md. Rifat Prediction of rainfall using data mining techniques |
| description |
This thesis report is submitted in partial fulfilment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2017. |
| author2 |
Tairin, Suraiya |
| author_facet |
Tairin, Suraiya Prema, Fahmida Tasnim Ahmed, Sharmin Islam, Md. Rifat |
| format |
Thesis |
| author |
Prema, Fahmida Tasnim Ahmed, Sharmin Islam, Md. Rifat |
| author_sort |
Prema, Fahmida Tasnim |
| title |
Prediction of rainfall using data mining techniques |
| title_short |
Prediction of rainfall using data mining techniques |
| title_full |
Prediction of rainfall using data mining techniques |
| title_fullStr |
Prediction of rainfall using data mining techniques |
| title_full_unstemmed |
Prediction of rainfall using data mining techniques |
| title_sort |
prediction of rainfall using data mining techniques |
| publisher |
BRAC University |
| publishDate |
2018 |
| url |
http://hdl.handle.net/10361/9489 |
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AT premafahmidatasnim predictionofrainfallusingdataminingtechniques AT ahmedsharmin predictionofrainfallusingdataminingtechniques AT islammdrifat predictionofrainfallusingdataminingtechniques |
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