A prediction model for cruise tourism demand based on BP neural network

Abstract

Abstract: Scientific analysis on cruise tourism demand is the key issue to correctly guide the planning, investment, and development of the cruise industry. First, the method combining the qualitative research with quantitative analysis is used to identify the influential factors of cruise tourism demand. Based on the BP neural network, a model for forecasting the cruise tourism demand is built, and then the model is trained and tested on the basis of statistical data of U.S.A. cruise tourism market. Finally, a model that is used to forecast the demand of Chinese cruise tourism market is proposed and the results indicate that the prediction reaches at the precision above 95%.

Key words: cruise, tourism demand, influential factor, BP neural network

CLC Number:

F590.8

Jia Peng, Liu Ruiju, Sun Ruiping, Yang Zhongzhen. A prediction model for cruise tourism demand based on BP neural network[J]. Science Research Management, 2013, (6): 77-83.

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