Study On The Tourism Crisis Early Warning System In Network Image Of Scenic Spot Based On The Application Of BP Neural Network

The tourism industry is developing rapidly under the guidance of national policy.The internet has become an important strategic platform for national tourism development,and it has become an essential part of people's Daily life.Network research has become the key channel for tourists to obtain destination information,and an important source of tourism destination image construction.However,as a comprehensive industry,tourism has a wide coverage,influenced by many factors,and has a very high sensitive coefficient for the information asymmetry.Based on the characteristics and effectiveness of the network,tourism obtains the opportunities from the changes of the Internet development,but also increases potential factors in tourism crisis.As the basic unit of tourism destination,the opening of the network increases the expansion of the information sources,the comments from various tourists and even the users,the media reports on the macroscopic environment are common.The revelation of the tourism unexpected events is widely known as the coverage of the network.As the main platform of information collection,the existence of these information sources has changed the scenic spot's traditional mode of transmission which is more propaganda single and official,changed the phenomenon in traditional information asymmetry,increased the sensitivity coefficient on the image of tourist scenic spot,and affected the traveler's decision-making behavior.Therefore,this paper took the scenic spot network image as the research object,discussed its crisis influence factors,constructed the early warning indicators which gave the most profound influence,combined with the data sample of related indexes,applied the BP neural network technology and established a warning system based on the BP neural network toolbox in the MATLAB for early warning simulation experiment and detection,it proved that the model had a good training performance and high warning accuracy.And provided suggestions on the crisis management of the scenic spot's network image form the view of managers,hoping to take new measures and new ideas for the sustainable development of tourism scenic spots.The conclusions of this study are as follows:Section 1: This paper explained the research background of the tourism development mode and the crisis management in the tourism scenic spot and points out the research goal,then analyzed the relevant results at home and abroad to determine the significance of the study and pointed out the characteristics of the current research and the existing problems,in this way to find out the entry point of this paper research,and make clear the significance of the research on the crisis early warning of tourism scenic spot.Section 2: This paper explained the relevant concepts and analysis of related theories to lay the theoretical foundation for the thesis writing.Combining with the research results at home and abroad,the paper defined the concept of tourist scenic spot,network image,tourism crisis and BP neural network and other related.After that this paper discussed the basic concepts of tourism crisis of tourist destination image and the relevant theories of BP neural Network algorithm theory to provide theoretical support for studying the construction of the early warning index and model construction of the network image crisis of scenic spots.Section 3: This paper constructed the early warning indicators.By the way of analyzing the situation of the relevant studies on the impacts of tourism destination image,the paper put forward the influence factors of the scenic spot network image from three levels,such as the network information's nature,the information's source and the information content and carried on the efficiency analysis to the influence factor.Then the paper further constructed the scenic spot network image influence factor model and established the index system about the scenic spot network image early warning.Section 4: Designed the image crisis early warning system based on BP neural network.First,this paper collected the sample data by use of web crawlers' software,NLPIR and other software,and then the simulation and training samples were obtained by the method of text content analysis and expert grading,next the BP neural network model was designed according to the research problem and then experimented and detected the model warning accuracy with the BP neural network toolbox in the MATLAB.Finally,the design of the network image crisis early warning scheme based on the BP neural network model is formed.Section 5: This paper put forward some suggestions on the network image crisis management of tourism scenic spots.Combining with early warning research results and crisis management model,this paper put forward the early warning management policy and management procedures from the management point of view.With the network text information can be quantified,the characteristics of the dissemination,put forward the crisis early warning strategy for tourism scenic spots network image,which is "monitoring and promotion online,management and promotion offline ".and the specific plan of the network image crisis of tourism scenic spot from the angle of crisis type.