Intelligent Prediction System of Sports Tourism Destination Demand Based on the Integration of Tourist Ecological Footprint Model

In view of the fact that the prediction of traditional sports tourism destinations is affected by the excessive entities and large dynamic changes of economic structure, this paper proposes a method of prediction of demand intellectualization for sports tourism destinations integrating tourist ecolo...

Full description

Saved in:
Bibliographic Details
Published in2018 International Conference on Robots & Intelligent System (ICRIS) pp. 270 - 273
Main Authors Yue, Jun, Xie, Xianzhi, Li, Zongkeng, Chen, Jiaqiang
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.05.2018
Subjects
Conferences
demand intellectualization
Intelligent systems
prediction
Robots
sports tourism destinations
tourist ecological footprint model (TEFM)
Online AccessGet full text

Cover

More Information
Summary:In view of the fact that the prediction of traditional sports tourism destinations is affected by the excessive entities and large dynamic changes of economic structure, this paper proposes a method of prediction of demand intellectualization for sports tourism destinations integrating tourist ecological footprint model (TEFM). It uses tourist ecological footprint model (TEFM) to optimize the non-linear characteristic indexes that affect the demand for sports tourism destinations, and then obtain the initial data for predicting the demand for sports tourism destinations. Then it adopts the multi-objective decision-making theory to conduct trade mediation for the long-term conflict of sports tourism destinations. Finally, through TEFM it makes compensation for sports tourism destinations for long-term conflicts. The analysis of experimental results shows that compared with other different models, the model designed in this paper has high prediction accuracy and can accurately predict the demand trend for sports tourism destinations.
DOI:10.1109/ICRIS.2018.00076