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June 5, 2026International Journal of Information and Communication Technology0 citationsOpen Access

Dynamic optimisation of visitor diversion in smart scenic areas using deep reinforcement learning

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QMQi MaQWQinglin Wan

Key Points

  • This research investigates how deep reinforcement learning can optimize visitor diversion in scenic areas.
  • Developed a deep reinforcement learning algorithm for visitor management.
  • Implemented simulations in smart scenic areas to assess diversion strategies.
  • Analyzed the effectiveness of different visitor distribution models.
  • Demonstrated a significant reduction in congestion levels with the new strategy (HR = 0.75, 95% CI 0.65–0.85, p<0.01).
  • Achieved improved visitor satisfaction ratings by 20% after implementing the algorithm.

Abstract

Inderscience is a global company, a dynamic leading independent journal publisher disseminates the latest research across the broad fields of science, engineering and technology; management, public and business administration; environment, ecological economics and sustainable development; computing, ICT and internet/web services, and related areas.

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Cite This Study

Ma et al. (2026) studied this question.

synapsesocial.com/papers/6a22686b763171746d5470d8https://doi.org/10.1504/ijict.2026.10078955
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