Abstract
Weather forecasting is an emerging domain that predicts the weather condition at a particular location at a particular time. Weather forecasting is considered as the most sensitive research field which facing a lot of real-time issues such as inaccurate prediction, lack of handling in huge data volume and inadequate in technology advancement. In this paper, we propose the SPRINT algorithm which is works with the principle of the decision tree. The experimental work is carried out with climate dataset and applied on WEKA tool. Based on the climate parameters such as Outlook, Temperature, Humidity, and Windy the data is classified into sunny, overcast and rainy. From the obtained result the weather is predicted, to prove the proposed methods of proficiency in accuracy level. Performance comparison is done with the existing method navie Bayes, both results are plotted on the graph. The outcome proves SPRINT algorithm is efficient and accurate in predicting the weather conditions.
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14 June 2022
This article has been retracted. Please see the Retraction Notice for more detail: https://doi.org/10.1007/s12652-022-04141-z
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This article has been retracted. Please see the retraction notice for more detail:https://doi.org/10.1007/s12652-022-04141-z
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Krishnaveni, N., Padma, A. RETRACTED ARTICLE: Weather forecast prediction and analysis using sprint algorithm. J Ambient Intell Human Comput 12, 4901–4909 (2021). https://doi.org/10.1007/s12652-020-01928-w
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DOI: https://doi.org/10.1007/s12652-020-01928-w