Research on Sustainable Tourism Forecasting Model for Juneau based on AHP-PSO and Dynamic Strategy
DOI:
https://doi.org/10.54097/55g9ex50Keywords:
Sustainable Tourism Prediction Model, AHP, Dynamic Adjustment Strategy, PSO.Abstract
Cruise ship tourists have provided significant revenue for the city of Juneau, Alaska. However, with the surge in visitor numbers and rising temperatures, issues such as overcrowding and glacier melting have emerged. Therefore, the development and implementation of sustainable tourism plans are urgent. In response, this study has developed a sustainable tourism forecasting model for Juneau, using particle swarm optimisation algorithms to simulate changes in various indicators from 2025 to 2046, in order to determine the optimal weight allocation. This study holds important theoretical and practical significance. Theoretically, it enriches the research on sustainable tourism models by incorporating dynamic constraints and long-term environmental changes. Practically, it offers a scientific reference for Juneau to achieve sustainable tourism development. The main innovations of this study include the integration of multi-dimensional factors in the model, the consideration of dynamic constraints and long-term environmental changes, and the exploration of cooperative strategies between tourism revenue distribution and infrastructure investment.
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