RESEARCH ON BIG DATA MINING OF AGRO-ECOLOGICALTOURISM UNDER ENVIRONMENTALPROTECTION AND SUSTAINABLE DEVELOPMENT CONCEPT

摘要

The excavated eco-tourism big data contains a lot of useless data,which not only consumes the analysis time,but also affects the data analysis results.In response to such problems,a method for mining eco-tourism big data for environmental protection and sustainable development is proposed.Laplace feature mapping method is used to reduce the dimensionality of agro-ecological tourism big data,and the agro-ecological tourism big data after dimensionality reduction is cleaned on the basis of time series analysis.Then the processed agro-ecological tourism big data are input into the convolutional neural network to obtain the corresponding parameter matrix by training the eco-tourism big data and construct a convolutional neural network model containing the Caffe framework.Finally,the big data mining of agro-ecological tourism is achieved.The experimental results show that the mining time of the proposed method in multiple iterations is less than 0.4s,and the obtained mining accuracy is higher than other methods,which promotes the industrialization and sustainable development of agro-ecological tourism.