CAJ | 학술논문

该研究运用多重分形消除趋势移动平均分析法（MF-DMA）分析了汶川大地震前后4年的九寨沟国内外游客时序波动趋势,发现九寨沟旅游市场具有长期记忆性和多重分形特征。进一步采用滑移窗口理论方法,分析了地震前后九寨沟国内外游客人数波动多重分形结构的时序演化过程。研究发现,虽然震后九寨沟旅游市场遭受沉重打击,但仅过了1年,以2009年5月12日为界,九寨沟旅游系统内在分形机制就逐步恢复到震前状态。通过对该现象的深入分析,研究受地震等自然灾害影响的旅游景区灾后市场恢复过程中出现的临界质点效应,认为具有分形特征的灾后景区旅游市场恢复是一个由量变到质变的相变过程。在这一演化过程中,旅游系统是否进入临界态,以及是否有引发相变的关键事件是起决定作用的两个关键要素。
해연구운용다중분형소제추세이동평균분석법（MF-DMA）분석료문천대지진전후4년적구채구국내외유객시서파동추세,발현구채구여유시장구유장기기억성화다중분형특정。진일보채용활이창구이론방법,분석료지진전후구채구국내외유객인수파동다중분형결구적시서연화과정。연구발현,수연진후구채구여유시장조수침중타격,단부과료1년,이2009년5월12일위계,구채구여유계통내재분형궤제취축보회복도진전상태。통과대해현상적심입분석,연구수지진등자연재해영향적여유경구재후시장회복과정중출현적림계질점효응,인위구유분형특정적재후경구여유시장회복시일개유량변도질변적상변과정。재저일연화과정중,여유계통시부진입림계태,이급시부유인발상변적관건사건시기결정작용적량개관건요소。
In recent years, a number of methods for forecasting the tourism market have been presented. These methods, which are valuable tools for understanding the stationary fluctuation of tourism systems, include the time series method, the econometric method, the artificial neural network and genetic algorithms. Multifractal detrending moving average method （MF-DMA） is a new nonlinear algorithm, which is usually used to analyze a one- dimensional multifractal or higher-dimensional multifractals. In our research, MF-DMA has been successfully used to characterize the temporal fluctuations in the number of daily domestic and foreign tourists in the Jiuzhai Valley in China. The examined data sets correspond to the number of daily Jiuzhai Valley tourists for the time period of January 1, 2007, to December 31, 2010. These data are provided by the Jiuzhai Valley Administration. We disaggregate the data into two time series for domestic and foreign tourists. The lengths of data are all 1460. They show that Jiuzhai Valley tourism markets are characterized by long-term memory and are multifractal in nature. We note that the multifractal spectra extracted from the two time series are slightly different. Muhifractality is stronger in the foreign tourists＇ time series than in the domestics＇. This means that the influx of foreign tourists is less linear and predictable than that of domestic tourists. To study the contributions of the long-range correlation on multifractality, we destroy the temporal correlations by randomly shuffling the original time series. After this shuffling procedure, what remains are data with exactly the same fluctuation distributions but without memory or correlation. It is shown that the strength of multifractality in the randomly shuffled time series is much smaller than that of the original time series. This shows that the inherent long-term correlation structures in both time series are the main origins of muhifractality. In addition, the major sources of multifractality are studied. Based on the sliding window concept, the time evolutions of the multifractal behavior of domestic and foreign tourists are analyzed and the influence of the Wenchuan earthquake on the Jiuzhai Valley tourism system dynamics are evaluated quantitatively. This study indicates that although the Jiuzhai Valley tourism system was seriously affected by the Wenchuan earthquake, the inherent dynamical mechanism of the tourism system has not fundamentally changed over the long term. By May 12, 2009, the Jiuzhai Valley tourism system＇ s fractal mechanism had gradually restored to its pre-earthquake state. This means that the Jiuzhai Valley tourism system has the ability to recover in a short time period. Through an in- depth analysis of this phenomenon, we found the critical particle effects on the post-disaster restoration and reconstruction of tourist attractions： a phase transition of quantitative change to qualitative change for tourism market post-disaster recovery, which has fraetal characteristics. In the evolution of the tourism system, two key elements play a decisive role： whether to enter a critical state, and the main events that lead to phase transitions.