An Implementation of Data Mining Technique for Weather Forecasting

Authors

  • Rakshanda Dharmik  BE Scholars, Department of Information Technology Priyadarshini Bhagwati College of Engineering, Nagpur, Maharashtra, India
  • Anjali Pandey  BE Scholars, Department of Information Technology Priyadarshini Bhagwati College of Engineering, Nagpur, Maharashtra, India
  • Shraddha Hude  BE Scholars, Department of Information Technology Priyadarshini Bhagwati College of Engineering, Nagpur, Maharashtra, India
  • Sneha Mankar  BE Scholars, Department of Information Technology Priyadarshini Bhagwati College of Engineering, Nagpur, Maharashtra, India
  • Prof. Manoj S. Chaudhari  Assistant Professor, Department of Information Technology Priyadarshini Bhagwati College of Engineering, Nagpur, Maharashtra, India

Keywords:

Weather Forecast, Data Mining, Classification, Supervised Learning, Implementation, Performance Study.

Abstract

Weather forecasting is a critical application in meteorology and has been a standout amongst the most logically and mechanically difficult issues the world over. In this paper, we research the utilization of data mining strategies in forecasting most extreme temperature and rainfall. Weather prediction approaches are tested by complex weather wonders with restricted perceptions and past data. Weather wonders have numerous parameters that are difficult to identify and measure. Expanding improvement on correspondence systems empowered weather forecast master systems to coordinate and offer assets and along these lines hybrid system has risen. Despite the fact that these upgrades on weather forecast, these master systems can't be completely dependable since weather forecast is primary issue.

References

  1. A.R.W.M.M.S.C.B. Amarakoon, "Effectiveness of Using Data Mining for Predicting Climate Change in Sri Lanka", 2010.
  2. Meghali A. Kalyankar, S. J. Alaspurkar, " Data Mining Technique to Analyse the Metrological Data", International Journal of Advanced Research in Computer Science and Software Engineering 3(2), 114-118, February – 2013.
  3. P.Hemalatha, "Implementation of Data Mining Techniques for Weather Report Guidance for Ships Using Global Positioning System", International Journal Of Computational Engineering Research Vol. 3 Issue. 3 , march 2013.
  4. Mohsen Hayati & Zahra Mohebi, Temperature Forecasting Based on Neural Network Approch, World Applied Science Journal 2(6) 613-620, 2007, ISSN 818-4952 ©IDOSI Publications 2007.
  5. S.S. De, University of Kolkata, Artificial Neural Network Based Prediction of Max. & Min.Temperature in the Summer-Monsoon month over India, Applied Physics Research, Vol.1, No.2,Nov-2009.
  6. Kit Yan Chan,’’ Neural-Network-Based Models for Short-Term Traffic Flow Forecasting Using a Hybrid Exponential Smoothing and Leven berg–Marquardt Algorithm", IEEE trans on intelligent transportation system, VOL. 13, NO. 2, pp.644-646,JUNE 2012.
  7. Stephen Dunne and Bidisha Ghosh," Weather Adaptive Traffic Prediction Using Neuro wavelet Models", IEEE trans on intelligent transportation system, VOL. 14, NO. 1, pp.370, MARCH 2013.
  8. D. Domanskam. Wojtylak, "Fuzzy Weather Forecast In Forecasting Pollution Concentrations".
  9. Bjarne K. Hansen And Denis Riordan,"Weather Prediction Using Case-based Reasoning And Fuzzy Set .
  10. Charles A. Doswell Iii And Robert A. Maddox, "The Role Of Diagnosis In Weather Forecasting" 11th Conf.Weather Forecasting And Analysis June 1986

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Published

2018-04-30

Issue

Section

Research Articles

How to Cite

[1]
Rakshanda Dharmik, Anjali Pandey, Shraddha Hude, Sneha Mankar, Prof. Manoj S. Chaudhari, " An Implementation of Data Mining Technique for Weather Forecasting, IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 3, Issue 3, pp.749-753, March-April-2018.