Temperature Prediction Analysis Using Forecasting Models In Chennai

Authors

  • J. Jenolin
  • S. Santha

Abstract

Time series forecasting is an essential tool for planning and decision-making. Various methods, ranging from traditional statistical models to soft computing and artificial intelligence approaches, have been developed to produce increasingly accurate forecasts. Recently, several techniques based on fuzzy and stochastic methods have been proposed for forecasting. In this paper, we discuss and compare the Song and Chissom model, Improved Hwang, Chen and Lee model, Auto Regressive Integrated Moving Average (ARIMA) and Artificial Neural Networks (ANN) on predicting temperature fluctuations in the Chennai district over a period from the year 2006 to 2024.

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References

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Published

2025-07-07

How to Cite

1.
Jenolin J, Santha S. Temperature Prediction Analysis Using Forecasting Models In Chennai. J Neonatal Surg [Internet]. 2025Jul.7 [cited 2025Jul.20];14(32S):3928-32. Available from: https://jneonatalsurg.com/index.php/jns/article/view/7530

Issue

Vol. 14 No. 32S (2025): Journal of Neonatal Surgery

Section

Original Article

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Copyright (c) 2025 Poonam Lal, Devanand H. Dongre

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