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- W2364962035 abstract "The accurate forecasting of daily visitor numbers can provide scientific and reliable basis for the decision-making management of scenic area.Due to various objective factors,the daily visitor numbers not only shows nonlinear characteristics but also has obvious seasonal characteristics.It is difficult to forecast daily visitor numbers accurately by the annual model because of the heavy fluctuation of annual daily data.In order to solve this problem,based on the distribution characteristics of daily visitor numbers of Huangshan scenic area,this paper established six classification forecasting models(January February and December,March June and November,April and May,July and August,September and October,official holiday).Through simulation by SVR and compared with annual model,the results showed that six classification models eliminated the jump and fluctuations obviously,and improved the forecasting precision effectively." @default.
- W2364962035 created "2016-06-24" @default.
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- W2364962035 date "2015-01-01" @default.
- W2364962035 modified "2023-09-25" @default.
- W2364962035 title "Forecasting of Daily Visitor Numbers Based on the Classification Model" @default.
- W2364962035 hasPublicationYear "2015" @default.
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