An Experiment in Weather Prediction for North East and South West Monsoon Over Chennai
S.Meganathan1, R.Bala Krishnan2, A.Sumathi3, S.Sheik Mohideen Shah4, J.Senthilkumar5

1S.Meganathan, Faculty of Computer Science and Engineering, SASTRA Deemed University, Kumbakonam, Tamilnadu, India.
2R.Bala Krishnan, Faculty of Computer Science and Engineering, SASTRA Deemed University, Kumbakonam, Tamilnadu, India.
3A.Sumathi, Faculty of Computer Science and Engineering, SASTRA Deemed University, Kumbakonam, Tamilnadu, India.
4S.Sheik Mohideen Shah, Faculty of Computer Science and Engineering, SASTRA Deemed University, Kumbakonam, Tamilnadu, India.
5J.Senthilkumar Faculty of Computer Science and Engineering, SASTRA Deemed University, Kumbakonam, Tamilnadu, India.

Manuscript received on 12 August 2019. | Revised Manuscript received on 17 August 2019. | Manuscript published on 30 September 2019. | PP: 4460-4465 | Volume-8 Issue-3 September 2019 | Retrieval Number: C6802098319/2019©BEIESP | DOI: 10.35940/ijrte.C6802.098319
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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: TThere is a growing demand for spot specific forecast. Presently this has to be extracted from the regional forecast based on synoptic models. Synoptic models require input from various observatories of regions or the country and the central analysis centre is required for generating the synoptic charts. But recently the authors have established the potential of local data alone as a continuous time scale for use in effective local forecast using data mining techniques. Following the same association rule mining and classifier approach is tried for the forecast of wet and dog days on North East Monsoon and South West Monsoon months for the Chennai region with Latitude 13°11′ N and Longitude 80°11′ E, a coastal station over Bay of Bengal in South India and results are presented.
Keywords: Association Rule Mining, Classifier Approach, Rainfall Forecast, Data Mining.

Scope of the Article:
Data Mining