• Dr.M.Sengaliappan
• D.Logasanjay

Weather forecasting is a critical aspect of modern life, affecting various industries and human safety. Traditionally, Numerical Weather Prediction (NWP) models have been employed, but machine learning approaches offer promising alternatives with increased accuracy and efficiency. In this paper, IT explore the applications of Support Vector Machines (SVM) and Artificial Neural Networks (ANN) to weather forecasting. SVM is evaluated for its performance in binary classification tasks (e.g., rain prediction), while ANN is used to exploit spatial and temporal patterns in meteorological data. The results indicate that ANN outperforms SVM in complex multi-variable scenarios, while SVM excels in simpler, low-dimensional tasks.

Weather Forecasting, Support Vector Machines (SVM), Artificial Neural Networks (ANN), Machine Learning, Meteorological Data.

"Weather Forecasting Using Support Vector Machines and Artificial Neural Networks", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 9, page no.e922-e927, September-2024, Available :http://www.jetir.org/papers/JETIR2409520.pdf

"Weather Forecasting Using Support Vector Machines and Artificial Neural Networks", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 9, page no. ppe922-e927, September-2024, Available at : http://www.jetir.org/papers/JETIR2409520.pdf