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Weather Prediction System Using KNN Classification Algorithm

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  • Yousif Elfatih Yousif

Abstract

Data Mining is a technology that facilitates extracting relevant and which have factors in common from the set of data. It is the process of analysis data from different perspectives and discovering problems, patterns, and correlations in data sets that are useful for predicting outcomes that help you make a correct decision. Weather Prediction is a field of meteorology that is created by collecting dynamic data related to the current state of the weather such as temperature, humidity, rainfall, wind. In this paper, we designed a system using a classification method by k-Nearest Neighbors algorithm for predict whether through previous data to determine the expected temperature and humidity the prediction results were compared with real results, the comparison was good and acceptable.

Suggested Citation

  • Yousif Elfatih Yousif, 2022. "Weather Prediction System Using KNN Classification Algorithm," European Journal of Information Technologies and Computer Science, European Open Science, vol. 2(1), pages 10-13, January.
    • Handle: RePEc:epw:comput:v:2:y:2022:i:1:id:10044
    DOI: 10.24018/compute.2022.2.1.44
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    References listed on IDEAS

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    1. David J. Hand & Heikki Mannila & Padhraic Smyth, 2001. "Principles of Data Mining," MIT Press Books, The MIT Press, edition 1, volume 1, number 026208290x, December.
    2. Fan, Cheng & Xiao, Fu & Wang, Shengwei, 2014. "Development of prediction models for next-day building energy consumption and peak power demand using data mining techniques," Applied Energy, Elsevier, vol. 127(C), pages 1-10.
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