Construction of Virtual Simulation Teaching Resources for Tourism Major Based on Neural Network Algorithm

The insufficient combination and integration of virtual experiment and physical experiment is not conducive to improving the quality of personnel training and practical innovation ability; Lack of standards and norms and limitations of sharing are not conducive to the overall planning and open sharing of teaching resources. This paper studies the construction of virtual simulation teaching resources for tourism majors based on neural network algorithm, and the resource integration method based on CNN (Convolutional Neural Network). MapReduce in the model adopts an improved MapReduce algorithm framework. In the process of Arduino learning, the design of resource integration method based on CNN mainly consists of two parts: the design of Arduino device identification program based on CNN and the construction of Arduino device learning resource database. The test results show that in Hadoop cluster, the application of the improved MapReduce algorithm model can obviously improve the data access speed and processing performance, and the overall time consumption after the improvement is reduced by 9.326%. This test shows that using this improved algorithm can improve the access speed and data processing performance of the storage model.