Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/38555
Title: Application of data mining techniques for Novel ensemble forecast of lead seven Days minimum and maximum surface air Temperature in Chennai india
Researcher: Ramesh K
Guide(s): Anitha R
Keywords: Predictive data mining
Statistical computational and machine learning tools
Upload Date: 1-Apr-2015
University: Anna University
Completed Date: 01/10/2014
Abstract: Evolution in data storage and large databases has generated an newlineimperative need for new techniques and tools for data analysis and knowledge newlinediscovery Statistical computational and machine learning tools have been newlineused by scientific community and researchers in the area of scientific data newlineanalysis Data mining is a data analysis technique which explores data and newlinediscovers meaningful information and knowledge Predictive data mining will newlinebe a good aid for weather forecasting which predicts the future state of the newlineatmosphere with the present state information newlineAmong weather elements surface air temperature is the key newlinedeterminant for vegetation animals and human livelihood in a particular newlinelocation of earth which also influences most atmospheric parameters like newlineprecipitation humidity pressure wind speed and wind direction Since newlinedeviations in surface air temperature claims many lives in the earth timely newlineprediction of minimum and maximum surface air temperature will help in newlineplanning and governing very hot and very cold climate However it is newlinechallenging because of the dynamic atmospheric parameters associated with newlinethe temperature event newlineIn the proposed work data mining technique based ensemble newlineforecast of lead seven days minimum and maximum surface air temperature is newlinedeveloped for the location Chennai India newline newline
Pagination: xxi, 175p.
URI: http://hdl.handle.net/10603/38555
Appears in Departments:Faculty of Science and Humanities

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04_acknowledgement.pdf17.5 kBAdobe PDFView/Open
05_content.pdf53.61 kBAdobe PDFView/Open
06_chapter1.pdf131.46 kBAdobe PDFView/Open
07_chapter2.pdf106.91 kBAdobe PDFView/Open
08_chapter3.pdf403.1 kBAdobe PDFView/Open
09_chapter4.pdf160.42 kBAdobe PDFView/Open
10_chapter5.pdf368.85 kBAdobe PDFView/Open
11_chapter6.pdf2.96 MBAdobe PDFView/Open
12_chapter7.pdf36.04 kBAdobe PDFView/Open
13_appendix.pdf30.23 kBAdobe PDFView/Open
14_reference.pdf451.36 kBAdobe PDFView/Open
15_publication.pdf50.82 kBAdobe PDFView/Open
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