A multi-agent simulator trained on pre-mobility visitor choice data predicts post-mobility spatial distributions in Wakayama Castle Park with cosine similarity above 0.7 by modifying distances or attractiveness.
A questionnaire- only counterfactual machine learning approach to assess the spatial im- pact of green mobility vehicles in urban parks: A wakayama castle case study
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Human-Flow Digital Twin for Predicting the Effects of Mobility Introduction on Visitor Circulation
A multi-agent simulator trained on pre-mobility visitor choice data predicts post-mobility spatial distributions in Wakayama Castle Park with cosine similarity above 0.7 by modifying distances or attractiveness.