Abstract
Objective: Taking Lijiang tourism as an example, to establish a tourism prospect prediction system, and to solve the difficulties related to tourism areas. [Methods] firstly, the dynamic prediction response model of Li jiang tourism market was constructed. Using the computer simulation program to carry out the actual model operation, predict the tourism prospect of Li jiang City and evaluate the prediction results. F results the grey parameter a of the total tourism revenue model of Li jiang from 2009 to 2011 was 0.572 3, the internal control parameter u was 0.3937, \({\text{Ru}}\left( {{\text{T}} + 1} \right) = 0.5633\,\,\exp \left( {0.5723{\text{T}}} \right)4 - 0.688\,\,{ }0.2009.2011\) the grey parameter a of the total tourism reception model of Li jiang was 0.1256, the internal control parameter u was \(344.3260,\,\,{\text{X}}\,\left( {{\text{t }}4 - 1} \right):3102.48\,\,3{ }5\) exp \(\left( {0.1256{\text{ t}}} \right) - 274{\text{i}}.\,\,283{ }\,\,5\). The test results of the two models show that the fitting degree is very good. At the same time, it is predicted that the total tourism revenue of Li jiang City will reach or exceed 13 billion yuan in 2011, and the total number of tourists will exceed 8.8 million. [Conclusion] the prediction system can accurately predict other tourist areas in the case of incomplete information.
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He, C. (2021). Research on the Effect of Tourism Regional Planning Based on Computer Simulation Analysis. In: Xu, Z., Parizi, R.M., Loyola-González, O., Zhang, X. (eds) Cyber Security Intelligence and Analytics. CSIA 2021. Advances in Intelligent Systems and Computing, vol 1342. Springer, Cham. https://doi.org/10.1007/978-3-030-70042-3_25
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DOI: https://doi.org/10.1007/978-3-030-70042-3_25
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