On Rural Typologies with Neural Network Method: Case Study on Xining Region

There are great differences between the rural areas of China, and rural areas themselves have complex development characteristics. With the implementation of the strategy of rural revitalization, ‘one-fits-all’ rural policy standards have had difficulty to meet the needs of different types of rural development. Rural policies adapted to local conditions cannot be separated from the identification of rural types. How to scientifically distinguish between rural areas and a widely ranged rural typology is of great significance. This paper attempts to introduce the artificial neural network method to identify rural types and to explore the impact of the neural network model trained with different sample data on the results of rural type recognition. Taking the Xining region as an example, rural types were identified and the applicability of the model was tested. Finally, the recognition results of the neural network model were examined and further improvement of the proposed method is discussed.