Forecasting of Jiangsu Inbound Tourism Demand Based on Composite Pattern

doi:10.3969/j.issn.1006-2475.2010.10.009

Computer and Modernization ›› 2010, Vol. 1 ›› Issue (10): 34-37.doi: 10.3969/j.issn.1006-2475.2010.10.009

• 人工智能 • Previous Articles Next Articles

Forecasting of Jiangsu Inbound Tourism Demand Based on Composite Pattern

SU Zhi-ping

Nanxu School, Jiangsu University of Science and Technology, Zhenjiang 212004, China

Received:2010-06-10 Revised:1900-01-01 Online:2010-10-21 Published:2010-10-21

Abstract

Abstract: Inbound tourism is the key factors of development to tourism industry. It is very important and necessary to improve reception efficiency and level of tourist destination that achieve a period of the tourist reception information by forecasting inbound tourism demand. The paper forecasts the inbound tourism demand of Jiangsu province by applying ARIMA model and BP neural network model to supply policy reference and data support for implementing the tourism development strategies of Jiangsu province. The results indicate that the forecast results are good.

Key words: ARIMA, BP neural network, inbound tourism, forecasting

CLC Number:

TP391
F590

SU Zhi-ping. Forecasting of Jiangsu Inbound Tourism Demand Based on Composite Pattern[J]. Computer and Modernization, 2010, 1(10): 34-37.

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Forecasting of Jiangsu Inbound Tourism Demand Based on Composite Pattern

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