Research On The Evaluation Of Urban Smart Tourism Service System

As global tourism road,new way of tourism rapid development,expandedthe tourist activity space and the "distance" greatly,with therequirementincreasingoftourists in the dependence of the informatization,visitors are paying more attention to tourism service level and quality,need to gain more accurate,effective,convenient and active servicetomeetour owntravel needs.Smart tourism is an important support to build modern tourismandtheservice industries,since the implementation of the national smart tourism pilot cities,they have basically built some websites and information systems,and some regions have realized information sharing,but the multi-dimensional tourism services in urban areas have not been substantial changed.There isfewresearchaboutsmarttourism service in our country,mostly focus on the management of smart tourism scenic spots,tourism experience and tourism resources.Therefore,this paper carry out a neural network for simulation to provide a research and evaluation method for detecting urban smart tourism services.Basic theorystudy.On the basis of literature review and conceptual analysis of smart tourism,urban tourism and tourism services,the concept of urban smart tourism service system is defined,and constructsevaluationsystemandmodel of urban smart tourism service system.Construct the evaluation system.The tourism components in the smart tourism service industry chain are classified and analyzed.The evaluation system system of the service system is analyzed in detail from the six elements of tourism,the supporting foundation of smart tourism network and information technology.Secondly,establish evaluation criteria.The evaluation standard of qualitative index adopts the authoritative indicator standard published by the official,and the data is obtained directly from the statistical data of relevant industries.The evaluation criteria of quantitative indexes are weighted by expert consultation.Construct the evaluation model.Taking BP neural network as the simulation model,this paper takes several cities as samples for the urban smart tourism service system,Part of the data collected through the use of Matlab software to realize learning and training,and finally compares the output results with the target value,and classifies them according to thenumericalsizeof the output value.Conductreal exampleanalysisto thecaseofthetypicalsample.After the training and learning of the neural network,the accurate weights and thresholds were obtained,and the samples were substituted into the evaluation test.The samples were selectedfrom the first batch of pilot cities of smart tourism with typical characteristics of smart tourism.Finally,the evaluation results of the neural network model are analyzed and feasible strategies and Suggestions are put forward.