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  • 标题:Rainfall Prediction using Data Mining Techniques: A Systematic Literature Review
  • 作者:Shabib Aftab ; Munir Ahmad ; Noureen Hameed
  • 期刊名称:International Journal of Advanced Computer Science and Applications(IJACSA)
  • 印刷版ISSN:2158-107X
  • 电子版ISSN:2156-5570
  • 出版年度:2018
  • 卷号:9
  • 期号:5
  • DOI:10.14569/IJACSA.2018.090518
  • 出版社:Science and Information Society (SAI)
  • 摘要:Rainfall prediction is one of the challenging tasks in weather forecasting. Accurate and timely rainfall prediction can be very helpful to take effective security measures in advance regarding: ongoing construction projects, transportation activities, agricultural tasks, flight operations and flood situation, etc. Data mining techniques can effectively predict the rainfall by extracting the hidden patterns among available features of past weather data. This research contributes by providing a critical analysis and review of latest data mining techniques, used for rainfall prediction. Published papers from year 2013 to 2017 from renowned online search libraries are considered for this research. This review will serve the researchers to analyze the latest work on rainfall prediction with the focus on data mining techniques and also will provide a baseline for future directions and comparisons.
  • 关键词:Rainfall prediction; data mining techniques; SLR; systematic literature review
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