Univ Nairobi, Nairobi, Kenya
With the rapid development of the economy, the tourism industry has been rapidly promoted, and the environmental pollution problems caused by the serious overloading of tourists have emerged in various tourist areas. Although it has effectively improved the development speed of tourism economy, it is not conducive to the ecological stability of local tourism areas. The sustainable economic growth of tourism needs to analyze the scenic resources and calculate the Carrying Capacity (CC) of the scenic resources. This refers to the level of tourism activities that can be supported by a specific tourism destination. The number of tourists that can be accommodated in the scenic spot can be estimated by investigating the environmental CC of the natural scenic spot, so as to ensure that the tourism development would not damage the environment of the scenic spot. The traditional analysis of Tourism Environmental Carrying Capacity (TECC) is based on artificial analysis indicators, which leads to inaccurate analysis of the environmental CC of tourism areas. With the development of Artificial Intelligence (AI) technology, this paper applied AI technology to the analysis of TECC of natural environment areas. This paper compared the traditional analysis of TECC with the analysis of TECC based on AI technology. The accuracy of the analysis of the TECC of the traditional natural environment area was the highest of 86.8%, and the accuracy of the analysis of the TECC of the natural environment area based on AI was the highest of 94.2%. Therefore, the application of AI technology to comprehensive analysis of various resource indicators of scenic spots could effectively improve the accuracy of environmental CC analysis of scenic spots.
Tourism Environmental Carrying Capacity, Natural Environment Area, Artificial Intelligence, Artificial Neural Network
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