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Despite the global sustainability trend, airport buildings have received limited attention regarding their environmental impact within the built environment and aviation sectors. With less than 1% of green building certifications worldwide, there is a lack of essential green performance assessment tools, including frameworks, primary datasets, and models that require less human supervision. Previous research has addressed these issues by proposing frameworks, primary datasets, and a supervised method that leverages Classification and Regression Trees. However, these methods still rely on human effort to fix credit scores and assign category weights, necessitating significant supervision from human experts. This study presents a green performance evaluation model for airport buildings using an explainable semi-supervised AI approach to reduce human dependency during the inference of green scores …