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RETRACTED ARTICLE: Weather forecast prediction and analysis using sprint algorithm

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This article was retracted on 14 June 2022

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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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References

  • Almgren K, Alshahrani S, Lee J (2019) Weather data analysis using hadoop to mitigate event planning disasters. https://scholarworks.bridgeport.edu/xmlui/handle/123456789/1105 Accessed 1 Feb 2019

  • Alshareef A, Bakar AA, Hamdan AR, Abdullah SMS, Jaafar O (2015) Pattern discovery algorithm for weather prediction problem. In: Science and Information Conference (Sai), IEEE, pp 572–577

  • Chen S-M, Hwang J-R (2000) Temperature prediction using fuzzy time series. IEEE Trans Syst Man Cybern B Cybern 30(2):263–275

    Article  Google Scholar 

  • Cuzzocrea A, Gaber MM, Fadda E (2019) (2019) An innovative framework for supporting big atmospheric data analytics via clustering-based spatio-temporal analysis. J Ambient Intell Human Comput 10:3383–3398

    Article  Google Scholar 

  • Kothapalli S, Totad SG (2017) A real-time weather forecasting and analysis. In: IEEE international conference on power, control, signals and instrumentation engineering (ICPCSI-2017), pp 1567–1570

  • Mahmood MR, Patra RK, Raja R, Sinha GR (2019) A novel approach for weather prediction using forecasting analysis and data mining techniques. In: Saini H, Singh R, Kumar G, Rather G, Santhi K (eds) Innovations in electronics and communication engineering. Lecture notes in networks and systems, vol 65. Springer, Singapore

    Google Scholar 

  • Manogaran G, Lopez D (2018) Spatial (2018) cumulative sum algorithm with big data analytics for climate change detection. Comput Electr Eng 65:207–221

    Article  Google Scholar 

  • Maqsood I, Khan MR, Abraham A (2004) An ensemble of neural networks for weather forecasting. Neural Comput Appl 13(2):112–122

    Article  Google Scholar 

  • Munmun B, Tanni D, Sayantanu B (2018) Weather forecast prediction: an integrated approach for analyzing and measuring weather data. Int J Computer Appl. https://doi.org/10.5120/ijca2018918265

    Article  Google Scholar 

  • Oury DTM, Singh A (2018) Data analysis of weather data using hadoop technology. In: Smart computing and informatics, Springer, Singapore, pp 723–730

  • Salman AG, Kanigoro B, Heryadi Y (2015) Weather forecasting using deep learning techniques. In: 2015 International conference on advanced computer science and information systems (ICACSIS), pp 281-285

  • Sarcevic P, Kincses Z, Pletl S (2019) (2019) Online human movement classification using wrist-worn wireless sensors. J Ambient Intell Human Comput 10:89–106

    Article  Google Scholar 

  • Taksande AA, Mohod PS (2015) (2015) Applications of data mining in weather forecasting using frequent pattern growth algorithm. Int J Sci Res (IJSR) 4(6):3048–3051

    Google Scholar 

  • Wang Z, Mujib ABM (2017) The weather forecast using data mining research based on cloud computing. J Phys 1:1–6

    Google Scholar 

Download references

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Correspondence to N. Krishnaveni.

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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

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