Improved multi-level fuzzy integrated assessment algorithm for tourism environment carrying ability based on cloud model

Author:

Lin Pao-Ching1,Huang Jui-Chan2,Ho Ping-Tsan3

Affiliation:

1. Chizhou University, Anhui, China

2. Department of Industrial Engineering and Management, National Kaohsiung University of Science and Technology, Kaohsiung City, Taiwan

3. Department of Tourism Management, National Kaohsiung University of Science and Technology, Kaohsiung City, Taiwan

Abstract

In recent years, tourism has developed rapidly and made great contributions to the economic enhancement of various regions; While tourism environment carrying ability assessment is the key to tourism sustainable development. The randomness and fuzziness of the traditional multi-level fuzzy comprehensive tourism environmental carrying ability assessment model cannot be combined effectively. In view of this, to construct a reasonable and objective assessment model, this study improves the multi-level fuzzy comprehensive tourism environmental carrying ability assessment model based on cloud model. The results indicate that the unimproved model judges that this tourism environment carrying ability level corresponds to level 2 for selecting tourism destination. And it is in a suitable load state. The evaluation results on the foundation of cloud model improved multi-level fuzzy comprehensive tourism environmental carrying ability assessment show that its Ex is 5.748, En is 1,296 and He is 0.1, which is between moderate to slightly overloaded, and the overall state is moderate, but there is a tendency to develop towards slightly overloaded. The evaluation results of the improved model are more intuitive in showing the carrying capacity of the tourism environment, and these evaluation results are more objective and reliable, which verifies the applicability of the research model. This research model provides a theoretical basis and data support for the study of tourism environment carrying capacity.

Publisher

IOS Press

Subject

Artificial Intelligence,General Engineering,Statistics and Probability

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