Data mining for evolution of association rules for droughts and floods in India using climate inputs
An accurate prediction of extreme rainfall events can significantly aid in policy making and also in designing an effective risk management system. Frequent occurrences of droughts and floods in the past have severely affected the Indian economy, which depends primarily on agriculture. Data mining i...
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ftindianacasci:oai:repository.ias.ac.in:125864 2023-05-15T17:35:28+02:00 Data mining for evolution of association rules for droughts and floods in India using climate inputs Dhanya, C. T. Nagesh Kumar, D. 2009 application/pdf http://repository.ias.ac.in/125864/ http://repository.ias.ac.in/125864/1/Journal%20of%20Geophysical%20Research%20%20Atmospheres%20-%202009%20-%20Dhanya%20-%20Data%20mining%20for%20evolution%20of%20association%20rules%20for%20droughts.pdf https://doi.org/10.1029/2008JD010485 en eng American Geophysical Union http://repository.ias.ac.in/125864/1/Journal%20of%20Geophysical%20Research%20%20Atmospheres%20-%202009%20-%20Dhanya%20-%20Data%20mining%20for%20evolution%20of%20association%20rules%20for%20droughts.pdf Dhanya, C. T. Nagesh Kumar, D. (2009) Data mining for evolution of association rules for droughts and floods in India using climate inputs Journal of Geophysical Research, 114 (D2). ISSN 0148-0227 QE Geology Article PeerReviewed 2009 ftindianacasci https://doi.org/10.1029/2008JD010485 2022-10-22T17:37:24Z An accurate prediction of extreme rainfall events can significantly aid in policy making and also in designing an effective risk management system. Frequent occurrences of droughts and floods in the past have severely affected the Indian economy, which depends primarily on agriculture. Data mining is a powerful new technology which helps in extracting hidden predictive information (future trends and behaviors) from large databases and thus allowing decision makers to make proactive knowledge-driven decisions. In this study, a data-mining algorithm making use of the concepts of minimal occurrences with constraints and time lags is used to discover association rules between extreme rainfall events and climatic indices. The algorithm considers only the extreme events as the target episodes (consequents) by separating these from the normal episodes, which are quite frequent, and finds the time-lagged relationships with the climatic indices, which are treated as the antecedents. Association rules are generated for all the five homogenous regions of India and also for All India by making use of the data from 1960 to 1982. The analysis of the rules shows that strong relationships exist between the climatic indices chosen, i.e., Darwin sea level pressure, North Atlantic Oscillation, Nino 3.4 and sea surface temperature values, and the extreme rainfall events. Validation of the rules using data for the period 1983–2005 clearly shows that most of the rules are repeating, and for some rules, even if they are not exactly the same, the combinations of the indices mentioned in these rules are the same during validation period, with slight variations in the classes taken by the indices. Article in Journal/Newspaper North Atlantic North Atlantic oscillation Indian Academy of Sciences: Publication of Fellows Indian Journal of Geophysical Research 114 D2 |
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Indian Academy of Sciences: Publication of Fellows |
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topic |
QE Geology |
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QE Geology Dhanya, C. T. Nagesh Kumar, D. Data mining for evolution of association rules for droughts and floods in India using climate inputs |
topic_facet |
QE Geology |
description |
An accurate prediction of extreme rainfall events can significantly aid in policy making and also in designing an effective risk management system. Frequent occurrences of droughts and floods in the past have severely affected the Indian economy, which depends primarily on agriculture. Data mining is a powerful new technology which helps in extracting hidden predictive information (future trends and behaviors) from large databases and thus allowing decision makers to make proactive knowledge-driven decisions. In this study, a data-mining algorithm making use of the concepts of minimal occurrences with constraints and time lags is used to discover association rules between extreme rainfall events and climatic indices. The algorithm considers only the extreme events as the target episodes (consequents) by separating these from the normal episodes, which are quite frequent, and finds the time-lagged relationships with the climatic indices, which are treated as the antecedents. Association rules are generated for all the five homogenous regions of India and also for All India by making use of the data from 1960 to 1982. The analysis of the rules shows that strong relationships exist between the climatic indices chosen, i.e., Darwin sea level pressure, North Atlantic Oscillation, Nino 3.4 and sea surface temperature values, and the extreme rainfall events. Validation of the rules using data for the period 1983–2005 clearly shows that most of the rules are repeating, and for some rules, even if they are not exactly the same, the combinations of the indices mentioned in these rules are the same during validation period, with slight variations in the classes taken by the indices. |
format |
Article in Journal/Newspaper |
author |
Dhanya, C. T. Nagesh Kumar, D. |
author_facet |
Dhanya, C. T. Nagesh Kumar, D. |
author_sort |
Dhanya, C. T. |
title |
Data mining for evolution of association rules for droughts and floods in India using climate inputs |
title_short |
Data mining for evolution of association rules for droughts and floods in India using climate inputs |
title_full |
Data mining for evolution of association rules for droughts and floods in India using climate inputs |
title_fullStr |
Data mining for evolution of association rules for droughts and floods in India using climate inputs |
title_full_unstemmed |
Data mining for evolution of association rules for droughts and floods in India using climate inputs |
title_sort |
data mining for evolution of association rules for droughts and floods in india using climate inputs |
publisher |
American Geophysical Union |
publishDate |
2009 |
url |
http://repository.ias.ac.in/125864/ http://repository.ias.ac.in/125864/1/Journal%20of%20Geophysical%20Research%20%20Atmospheres%20-%202009%20-%20Dhanya%20-%20Data%20mining%20for%20evolution%20of%20association%20rules%20for%20droughts.pdf https://doi.org/10.1029/2008JD010485 |
geographic |
Indian |
geographic_facet |
Indian |
genre |
North Atlantic North Atlantic oscillation |
genre_facet |
North Atlantic North Atlantic oscillation |
op_relation |
http://repository.ias.ac.in/125864/1/Journal%20of%20Geophysical%20Research%20%20Atmospheres%20-%202009%20-%20Dhanya%20-%20Data%20mining%20for%20evolution%20of%20association%20rules%20for%20droughts.pdf Dhanya, C. T. Nagesh Kumar, D. (2009) Data mining for evolution of association rules for droughts and floods in India using climate inputs Journal of Geophysical Research, 114 (D2). ISSN 0148-0227 |
op_doi |
https://doi.org/10.1029/2008JD010485 |
container_title |
Journal of Geophysical Research |
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114 |
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D2 |
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1766134640888774656 |