Global Planning Method of Village Public Space Based on Deep Neural Network

The current overall planning method of village public space is inefficient in land integration, resulting in poor planning effect. In order to solve the above problems, a global planning method of village public space based on deep neural network is proposed. Firstly, the hidden neurons are determined by using the data information obtained from the deep neural network, the green coefficient and spatial comfort are extracted, and the change value of the load curve is calculated at the same time, and the data is filtered. Then, the land planning is realized through data analysis, data preprocessing, rural land planning mapping database and the update mechanism of the database, and the variation coefficient is determined, and the standard deviation is calculated; Finally, the global planning is realized through neural network. The experimental results show that the proposed method can effectively improve the efficiency of land integration and plan a user satisfactory scheme.