A Study on Exponential Smoothing Method for Forecasting

Authors

  • Shastri S Dept. of CS&IT, Kathua Campus, University of Jammu, J&K, India
  • Sharma A Dept. of CS&IT, Kathua Campus, University of Jammu, J&K, India
  • Mansotra V Dept. of CS&IT University of Jammu, J&K, India
  • Sharma A Dept. of IT & Research, UCCA, Guru Kashi University, Talwandi Sabo, Punjab
  • Bhadwal AS Dept. of CS&IT, Ramnagar Campus, University of Jammu, J&K, India
  • Kumari M Dept. of CS&IT, Kathua Campus, University of Jammu, J&K, India

DOI:

https://doi.org/10.26438/ijcse/v6i4.482485

Keywords:

Data Mining, BCG, Time Series data, Exponential Smoothing

Abstract

Data mining is one of the most essential steps of Knowledge Discovery process that is required to extract interesting patterns from enormous size of data. In this paper, we have used the BCG coverage data i.e. Percentage of live births who received Bacillus Calmette Guerin (BCG) a vaccine against tuberculosis and forecast the BCG coverage percentage for the next five years based on historical yearly data of BCG coverage in India by using the exponential smoothing technique of forecasting. Exponential Smoothing is a well-liked forecast technique that uses weighted values of previous series observations to predict the immediate future for time series data. The aim of this paper is to study the exponential smoothing method of time series for forecasting purpose.

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Published

2025-11-12
CITATION
DOI: 10.26438/ijcse/v6i4.482485
Published: 2025-11-12

How to Cite

[1]
S. Shastri, A. Sharma, V. Mansotra, A. Sharma, A. S. Bhadwal, and M. Kumari, “A Study on Exponential Smoothing Method for Forecasting”, Int. J. Comp. Sci. Eng., vol. 6, no. 4, pp. 482–485, Nov. 2025.

Issue

Vol. 6 No. 4 (2018): IJCSE April Edition

Section

Research Article

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