Air temperature estimation and modeling using data driven techniques based on best subset regression model in Egypt.

A notable trend in the results is that SVM appears to be significantly different from most models, often with large negative Sum Rank Differences, indicating poorer performance relative to others.

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By integrating machine learning models and climate projections, the results highlight an increasing trend in temperature and evapotranspiration across all scenarios.

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However, the comparisons between “Actual” and other models, such as Random Subspace ( p < 0.001), Linear Regression ( p < 0.001), M5P ( p < 0.001), and SVM ( p < 0.001), exhibit highly significant differences, indicating that these models differ considerably from the actual values.

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