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Based on the boarding and alighting ridership data collected at 236 subway stations in Beijing, a cluster analysis method is used to divide them into nine categories. The two-factor variance test shows the feasibility of the proposed category and indicates that there are significant differences among different category of subway stations. The characteristics of surrounding population, employment, and land use of each category of subway station were further investigated and the results demonstrate that different land use development surrounding different category of subway stations lead to significant difference with respect to observed time distribution of entering and exiting ridership.
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Stored only when both papers are in the corpus — 17 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
Imported from OpenAlex (CC0) — nothing here is generated.