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Traffic Flow Forecast for Grassland Tourism Highway in Inner Mongolia

Author: LiuChenHui
Tutor: QiChunHua
School: Inner Mongolia Agricultural University
Course: Forest Engineering
Keywords: Inner Mongolia Forest Tourism Highway Traffic Flow Forecast Artificial neural network forecasting method
CLC: F592
Type: Master's thesis
Year: 2010
Downloads: 78
Quote: 0
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Abstract


With the development of western social and economic level, the grassland culture’s influence has expanded widely and the grassland tourism has been developed fast, especially the tourism of the Inner Mongolia regions has been developed much faster. The growth of the tourism in Inner Mongolia has improved the region’s requirements of the grassland tourist highway. The program and construction of grassland are based on traffic flow forecast. At present the research on the general road traffic flow forecast has matured. But the theory of grassland tourist highway has lacked. Based on protecting the ecological environment and combining the characteristics of Inner Mongolia grassland tours, the study about grassland tourism highway traffic flow has been carried out, which contributes to overall plan of tourism Highway in Inner Mongolia. It has great significance to construct the transportation system, to attract more tourists, to develop tourism industry and to develop economic of the Inner Mongolia.On the basis of extensive reference, the author proposed that the features of Inner Mongolia grassland tourism highway are as follow:the number of tourist varies with the different season. At the tourism peak, traffic volumes grow rapidly, which results in traffic congestion. But in the tourist depression season, traffic volumes grow slowly, which results in transport facilities are unused abundantly. On this basis, There are 11 factors impacting travel highway traffic flow by analyzing their characteristics such as tourism revenues, the number of travel agencies, the length of road transport routes, the number of passengers, road passengers, traffic passengers each day, passenger vehicles, the number of undergraduates in per million population, the absolute number of whole consumption level, the household consumption expenditure of farmers and herdsmen and the consumption expenditure of town residents. How the 11 factors are associated with the number of tourists is quantitative analyzed by using SPSS software, and then these factors are asserted the traffic flow by their correlation.Based on the analysis of characteristics of time series prediction method, regression prediction method, the gray prediction method and BP artificial neural network forecasting method, thinking of the characteristics of tourist highway in Inner Mongolia, this author adopts BP to forecast tourists of international and domestic tourists then forecast tourists in 2010. Then the traffic flow is forecast with the formula which the author establishes to change the number of tourists into traffic flow. By analyzing that BP neural network predictive model compares with three examples of the trend prediction method, the author finds that the BP neural network predictive model is better. The BP neural network was help to travel to Inner Mongolia grasslands road master plan, to develop the Inner Mongolia tourism industry and to build tourism transport system.

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