Weather Prediction Using Machine Learning  Techniques

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Ayush Raj; Ms. Vartika Mishra

Weather Prediction Using Machine Learning Techniques

Authors: Ayush Raj, Ms. Vartika Mishra

Unique Paper ID: 180793
Volume: 12
Issue: 1
PageNo: 2656-2660

Keywords: Machine Learning Ridge Regression Weather Prediction Numerical Weather Prediction (NWP) Feature Engineering Data Preprocessing Climate Data Predictive Modeling Time Series Analysis Rolling Averages Seasonal Trends Backtesting Mean Absolute Error (MAE) Mean Squared Error (MSE) Multicollinearity Data Imputation Weather Metrics

Abstract:
This research focuses on predicting weather patterns using Machine Learning techniques to improve forecasting accuracy. Traditional weather predictions rely on Numerical Weather Prediction (NWP) models, which have limitations in precision due to their reliance on complex equations and computational demands. In this study, a Ridge Regression model is applied to historical weather data to predict maximum daily temperatures, leveraging various weather metrics (e.g., temperature, precipitation) and rolling averages. The results demonstrate that the ML-based approach offers comparable accuracy to conventional methods, with potential for enhancements in real-time prediction efficiency and usability.

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Cite This Article

ISSN: 2349-6002
Volume: 12
Issue: 1
PageNo: 2656-2660

Weather Prediction Using Machine Learning Techniques

Available:https://ijirt.org/article?manuscript=180793

Impact Factor
8.01 (Year 2024)

UGC Approved
Journal no 47859

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