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Generating equitable urban human flows with a fairness-aware deep learning model
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DOI：10.1016/j.cities.2025.106296.png)
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Abstract
En 中文
• FairMobi-Net: a fairness-aware deep learning model for human flow generation. • Integrates fairness loss to reduce income-based regional disparities. • Outperforms state-of-the-art models in four U.S. metropolitan areas. • Ensures more equitable and consistent performance in underserved regions.
Keywords:
Human mobility
Fairness-aware flow generation
Urban mobility flows
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