Extreme Precipitation Events in Chennai Metro City Using Data Mining
R. Senthil Kumar1, C. Ramesh2
1R.Senthil Kumar, Research Scholar, Department of Computer Science and Engineering, Satyabama University, Chennai.
2Dr. C. Ramesh, Research Supervisor, Satyabama University,Chennai.
Manuscript received on 05 September 2019. | Revised Manuscript received on 22 September 2019. | Manuscript published on 30 September 2019. | PP: 99-108 | Volume-8 Issue-11, September 2019. | Retrieval Number: J99780881019/2019©BEIESP | DOI: 10.35940/ijitee.J9978.0981119
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: A information mining approach is displayed and connected to examine the climatic reasons for outrageous climatic occasions. Our methodology involves two primary strides of information extraction connected progressively, so as to decrease the trouble of the first informational index. The objective is to recognize an a lot littler subset of climatic factors that may in any case have the option to portray or even anticipate the outrageous occasions. The initial step applies a class correlation strategy. The subsequent advance comprises of a choice tree learning calculation utilized as a prescient model to outline set of measurably most huge atmosphere factors recognized in the past advance to classes of precipitation quality. The procedure is utilized to the investigation the climatic reasons for two outrageous occasions happened in India the most recent decade: the Chennai 2015 extraordinary precipitation disaster and the Tamilnadu(except Chennai) inadequacy of 2016. In the two cases, our outcomes are in great concurrence with investigations distributed in the writing.
Keywords: Extreme event, Drought, Intense rainfall, KDD (Knowledge Discovery in Databases), Data mining, Classification, Decision tree.
Scope of the Article: