International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Monthly Journal for Science , Computer Science and Engineering

Volume5,February 2018,

Topic : Weather Forecasting Using Data Mining

Authors:Siddhant Revankar || Shaba Desai

Abstract:Changing Climatic conditions are leading to alternate weather patterns. Accurately predicting weather patterns is important as they have wide social and economic impact. This paper proposes and analyzes a predictive model which analyse a wide range of data points with the aim of predicting likelihood and pattern of location-specific rainfall at a high degree of confidence. We extract knowledge from historical weather data collected from NOAA(National Oceanic Atmospheric Administration)[10]. From the collected weather data comprising of 15 attributes, only 5 attributes are most relevant to rainfall prediction. Data preprocessing and data transformation on raw weather data set is performed, so that it shall be possible to work on Bayesian and K-NN the data mining, prediction model used for rainfall prediction. The model is trained using training dataset and tested on test data for accuracy. We have used comparative approach of Bayesian and K-NN models and found Bayesian approach to be more accurate. .

Keywords: Rainfall prediction, Naive Bayes, K-Nearest Neighbor, Climate change, Weather patterns

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DOI: 01.1617/vol5/iss2/pid19802


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Editor-in-Chief

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Dr. Allon Guez
Professor, Drexel University,
USA


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IMPACT FACTOR: 4.890

ISSN(Online):2394-2320

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Thomson Reuters ID : q-6288-2016.
ORCiD Research ID : 0000-0001-9540-6799

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ACCEPTANCE RATIO: 28.69%
ARTICLES PUBLISHED:0521
PAPER RECEIVED:01730
Journal Code : IJERCSE
Electronic ISSN : 2394-2320
Impact Factor : 4.890
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