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  1. University of Computer Studies, Yangon
  2. Conferences

Big Data Analytics for Rainfall Prediction using MapReduce-Based Regression Model

http://hdl.handle.net/20.500.12678/0000004779
http://hdl.handle.net/20.500.12678/0000004779
97af947f-6959-480d-af1b-e7fd5bcce87b
b0e1fe5c-7cdf-4810-a191-f8154acc9b0b
Publication type
Article
Upload type
Publication
Title
Title Big Data Analytics for Rainfall Prediction using MapReduce-Based Regression Model
Language en
Publication date 2017-02-16
Authors
Khine, Kyi Lai Lai
Nyunt, Thi Thi Soe
Description
The most significant climatic element whichimpacts on agriculture sector is rainfall and rainfallprediction becomes an important issue in agriculturecountry like Myanmar. Collecting, storing andprocessing of huge amount of climatic data (BigData) require high-performance analytical systemsrunning on distributed environments for accurateprediction of weather. Traditional standard dataanalytics algorithms need to be adapted to takeadvantage of cloud computing models which providescalability and flexibility. In this paper, MultipleLinear Regression which is an empirical, statisticaland mathematically mature method in data analysisis applied in Rainfall Prediction. To proveconventional Multiple Linear Regression workefficiently in distributed environments, we propose aparallel processing of Regression Model calledMapReduce-based Multiple Linear Regression (MRMLR).Weekly Rainfall Prediction with the proposedregression model using large scale weather data willbase on the QR Decomposition and Ordinary LeastSquares method adapted to MapReduce Framework.Correlation-based Filter Approach by usingSymmetrical Uncertainty (SU) will be applied inselecting correlated and relevant features forimproving the proposed regression model’sprediction accuracy.
Keywords
Big data, Rainfall Prediction, Multiple Linear Regression, QR Decomposition, Ordinary Least Squares, Symmetrical Uncertainty
Identifier http://onlineresource.ucsy.edu.mm/handle/123456789/669
Journal articles
Fifteenth International Conference on Computer Applications(ICCA 2017)
Conference papers
Books/reports/chapters
Thesis/dissertations
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