Author(s)

Yulu Yang ¹, Wanli Cheng ¹

Affiliation(s)

¹ College of Water Resources and Architectural Engineering, Northwest A & F University, Yangling, Shaanxi, 712100

Corresponding Author

Yulu Yang

ABSTRACT

In this paper, gray prediction is used to predict the later development data of the year without the participation of the National Games, which is compared with the real value of the later year. Then fit all provinces with tourism data in China with the data in Shaanxi Province, and select the better fitting provinces Jiangxi, Shanxi and Yunnan as the standard to test the gray prediction results. For the area substitution error in gray prediction, Lagrange interpolation is used to calculate a new background value for optimization. Finally, the map line of tourism development growth rate is drawn, and the impact of the National Games on Shaanxi tourism is -15%.

KEYWORDS

Gray prediction, GM(1,1), LagRange interpolation theory

CITE THIS PAPER

Yulu Yang, Wanli Cheng. Research on the Tourism Industry Impact of the National Games Based on Grayscale Models. Tourism Management and Technology Economy (2021) 4: 21-26. DOI: http://dx.doi.org/10.23977/tmte.2021.040204.

REFERENCES

[1] Si Shoukui. Sun Zhaoliang. Mathematical modeling algorithms and applications. Beijing: National Defense Industry Press. 2015.
[2] Yan Zefan, Wang Chongyang, Wang Yonghao. Quantitative evaluation of the influence of Tangshan Expo based on grey prediction model [J]. Information Recording Materials, 2018, 19(05): 217-218.
[3] Tian Zichen, Ji Gang, Liu Miao. Analysis and prediction of Xinjiang's total population based on improved grey GM(1,1) model [J]. Mathematics in Practice and Knowledge, 2021, 51(05): 258-264.
[4] Wang Dan. Quantitative assessment of the impact of major events on the host city’s GDP [J]. Science & Technology Economic Guide, 2020, 28(17): 8-9.

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