Research On Evaluation Model Of Red Tourism Resources In Hunan Province Based On BP Neural Network

The red tourism resources in Hunan province are unique and rich in revolutionary culture resources.It is one of the important sources of red tourism resources.The red tourism resources evaluation is based on the perspective of the red resources,a comprehensive evaluation of its dissemination value,cultural value,economic value,educational value,all-round,multi angle,to construct a scientific and reasonable evaluation model,which can be used for the development and utilization of red tourism resources provide evidence.Red tourism resources evaluation influences by a variety of factors,and the evaluation process is a nonlinear program with many variables and high complexity.At present,the evaluation method is more analytic hierarchy process,fuzzy comprehensive evaluation method,These methods can obtain more objective and authentic evaluation results,need further improvement.The use of BP neural network can realize the intelligent evaluation of the red tourism resources,especially the untapped red tourism resources(such as the Long March line,the Tea Horse Road and the Hunan peasant movement,etc.),and avoid the subjective stochastic factors effectively.Evaluation of red tourism resources.Based on the basic theory of BP neural network,this paper introduces the general situation of model training data source(Hunan red tourism resources)from the three perspectives of type,distribution and overall characteristics,and constructs the evaluation model of red tourism resources in Hunan province Index system,used to collect experts on the selected scenic scoring data,and as a BP neural network model of input data.The index system is divided into six dimensions: ornamental,social,economic,artistic and cultural,political education and social emotional value,and 17 specific indicators.The three layers of BP neural network model with the order of 17(input layer),14(hidden layer)and 1(output layer)are constructed,and the normalized processing is input.The data are trained until the error is less than 0.001,indicating that the training is completed and the final neural network model is obtained.Finally,the data of Shaoshan scenic spot,Yang Kaihui's former residence and the hometown of Hu Yaobang are used to test the trained neural network model,and the score is 0.69914,0.60021,0.57988.The final rating is "good" or close to“good”,which proves that the overall red resource is in good condition and is in accordance with the actual quality assessment level.It also shows that the BP neuralnetwork evaluation model constructed by the article can be used for the excavation,evaluation and protection of red tourism resources.