In this study, the method of a fuzzy comprehensive evaluation is used to analyze the research situation of smart city development, and 20 evaluation indicator systems are selected as the original indicator database; the relevant sustainable development indicator data of prefecture-level cities in the first batch of smart city pilots are collected and normalized after processing. It is used as a sample library for correlation, reliability, validity test, weight calculation, and a benchmark value for evaluation model training. By processing the original indicator database data, the membership function of the indicator is constructed, and the fuzzy set theory is used for indicators. Classify and analyze the indicators according to the model to complete the collection of the indicator database; use the neural network model to determine the weight of each indicator in the indicator system. An indicator system and evaluation model for the sustainable development of smart city construction have been constructed. To ensure the actual effectiveness of the application of the indicator system, this study has conducted in-depth research on the influencing factors and principles of the system construction, and based on this, the design of the indicator system has been carried out. At the same time, for the determination of the sustainable development weight of the sustainable development system, the analytic hierarchy process was adopted through multiple considerations, and finally, the fuzzy comprehensive evaluation model for the sustainable development of smart city construction was constructed. The model in this study is innovative in research methods and research objects. It can provide a reference value for the development of smart cities and also help the change and innovation of the existing smart city evaluation index system.
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