Climate Change Modeling Using Machine Learning Techniques: Improving Prediction Accuracy in Environmental Science
Keywords:
Climate change modeling, machine learningAbstract
Accurate climate change prediction is essential for environmental planning and policy formulation. Traditional climate models, while scientifically robust, often face limitations in handling large-scale nonlinear datasets. This study evaluates the effectiveness of machine learning (ML) techniques in improving climate prediction accuracy compared to conventional statistical models. Using multi-year climate datasets, ML-based models demonstrated superior predictive performance, reduced error margins, and enhanced adaptability to complex environmental variables. The findings support the integration of machine learning approaches into contemporary climate science research.
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