<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>Man and nature are interconnected and interdependent. The naturalization of man reflects the scientific nature of the landscape, the development of ecotourism is to establish the development of man and nature in harmony and unity of the development of ideas. This paper proposes measures to enhance the tourism experience based on the above concept. After a series of operations, such as similarity calculation and data cleaning, the user category, consumption level, and geographic location preference are calculated to establish a user model and portrait based on behavioral analysis. Based on LASSO penalty regression, the link between covariates is incorporated into the penalty term to complete the optimization and improvement of the LASSO regression model. Associate the user preference degree model with the tourism demand prediction model based on user preference. The model is applied in practice, and the average error rate for the number of tourists predicted by the LASSO regression coefficient is about 9.9%, which is smaller than the average error rate of the comparison model. Based on the results of the demand prediction, strategies related to the development of sports tourism projects are proposed, and the impact of sports tourism projects on the environment is evaluated. Based on the IPA analysis method, the user’s tourism experience of the subject area is assessed, and the user is more concerned about the internal transportation of the tourist place, with I and P values of 12.455 and 1.457, respectively, and the performance effect of the subject area in this point is poor, which needs to be solved in time.</p>
</abstract>

Man and nature are interconnected and interdependent. The naturalization of man reflects the scientific nature of the landscape, the development of ecotourism is to establish the development of man and nature in harmony and unity of the development of ideas. This paper proposes measures to enhance the tourism experience based on the above concept. After a series of operations, such as similarity calculation and data cleaning, the user category, consumption level, and geographic location preference are calculated to establish a user model and portrait based on behavioral analysis. Based on LASSO penalty regression, the link between covariates is incorporated into the penalty term to complete the optimization and improvement of the LASSO regression model. Associate the user preference degree model with the tourism demand prediction model based on user preference. The model is applied in practice, and the average error rate for the number of tourists predicted by the LASSO regression coefficient is about 9.9%, which is smaller than the average error rate of the comparison model. Based on the results of the demand prediction, strategies related to the development of sports tourism projects are proposed, and the impact of sports tourism projects on the environment is evaluated. Based on the IPA analysis method, the user’s tourism experience of the subject area is assessed, and the user is more concerned about the internal transportation of the tourist place, with I and P values of 12.455 and 1.457, respectively, and the performance effect of the subject area in this point is poor, which needs to be solved in time.

Demand Forecasting and Project Development of Sports Tourism Based on User Behavior under the Perspective of Harmonious Coexistence of Human and Nature

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

Man and nature are interconnected and interdependent. The naturalization of man reflects the scientific nature of the landscape, the development of ecotourism...

Demand Forecasting and Project Development of Sports Tourism Based on User Behavior under the Perspective of Harmonious Coexistence of Human and Nature

Online veröffentlicht: 05. Aug. 2024

Seitenbereich: -

Eingereicht: 25. Apr. 2024

Akzeptiert: 11. Juli 2024

DOI: https://doi.org/10.2478/amns-2024-2248

Schlüsselwörter
Similarity calculation, Behavioral analysis, User profiling, LASSO penalized regression, Tourism demand forecasting, Tourism project development

© 2024 Yuhan Hu, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Demand Forecasting and Project Development of Sports Tourism Based on User Behavior under the Perspective of Harmonious Coexistence of Human and Nature

Online veröffentlicht: 05. Aug. 2024

Seitenbereich: -

Eingereicht: 25. Apr. 2024

Akzeptiert: 11. Juli 2024

DOI: https://doi.org/10.2478/amns-2024-2248

SchlüsselwörterSimilarity calculation, Behavioral analysis, User profiling, LASSO penalized regression, Tourism demand forecasting, Tourism project development

© 2024 Yuhan Hu, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Schlüsselwörter
Similarity calculation, Behavioral analysis, User profiling, LASSO penalized regression, Tourism demand forecasting, Tourism project development