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- W2340652936 abstract "Tourist number is one of the important factors which determine the sustainable development of economic efficiency, so tourist number forecast become an important content for tourism development planning. Based on least square support vector machine (LS-SVM) algorithm, this paper establish a new forecast model for tourist number, and predict the domestic tourist number of 2010 in Gansu province, China, and compare the forecast results of the neural network model and LS-SVM algorithm. The results show that LS-SVM forecasting model can accurately predict the number of tourism, and avoid the problems such as neural network which lost in local optimum when learning, and provide a new ideas and method for tourist forecast." @default.
- W2340652936 created "2016-06-24" @default.
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- W2340652936 date "2013-11-01" @default.
- W2340652936 modified "2023-09-23" @default.
- W2340652936 title "Tourist Number Forecast of Gansu Province Based on LS-SVM" @default.
- W2340652936 doi "https://doi.org/10.1109/mines.2013.178" @default.
- W2340652936 hasPublicationYear "2013" @default.
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