A fuzzy control model based on BP neural network arithmetic for optimal control of smart city facilities

In order to analyze and study the fuzzy control model of smart city optimization control, this paper designs a fully networked fuzzy controller based on BP neural network arithmetic, so that the realization process of fuzzy reasoning is networked and clear. The evaluation mode of wisdom town is constructed, and the index system is simplified according to the evaluation index system of the develop possible of wisdom town. The analog outcome shows that the above arithmetic can availably optimize the parameters and structure of the neuro vagueness control, and the designed neuro vagueness control has good performance. The build of wisdom cities is advantageous to further promoting the deep integration of industrialization, informationization, urbanization, and agricultural modernization, which is of great significance for solving urban development problems and promoting continuable town develop. To improve the development capacity of intelligent city, we should highlight the characteristics of smart cities; advocate the concept of sustainable development and low-carbon development, market-oriented, overall planning, top-level design, and micro-regulation; and take the road of development with local characteristics.