Research On Tourism Emergencies Clustering

As the scale and scope of national tourism become wider and wider these days, tourism has become the backbone industry in many districts. The development of tourism extremely depends on the stability of the external environment; many kinds of tourism emergencies can lead to crisis of tourism. This thesis is supported by National Natural Science Foundation of China and Beijing Natural Science Foundation and does the research on tourism emergencies clustering. The main work done in the thesis is as follows:(1) The research on tourism emergencies and the clustering scheme about them: the existing tourism emergencies clustering schemes are studied, and the problem of which is found through analyzing a single event, then a practical, coverall and based on divinable and governable property cluster scheme is introduced.(2)Improved K-means algorithm: the algorithm based on the artificial immune algorithm is introduced to solve the problem that the K-Means algorithm is easy to fall into local optimum. The algorithm based on the ball tree is introduced to solve the large computation in the text clustering. Bayesian Information Criterion is introduced to evaluate the quality of the clustering; then the result of the clustering is evaluated.(3)The text clustering application in the tourism emergencies: the text is portioned into words, and the dimension of characteristic words is reduced according to the part of speech, then the weight of the characteristic words is calculated, and the whole process is achieved using Python. The isolated points of the numerical information is clear using DBScan algorithm, finally, the result is got through the optimized algorithm. In this thesis a kind of practical clustering scheme is provided for tourism emergency management, and the corresponding measures are provided for different kinds of events to ensure the continued smooth development of the tourism industry. The more accurate measure can be got through the research on the tourism emergencies of different properties and sorts.