Innovation of Urban Circular Economy Growth Path Based on Neural Network - Weifeng Qiu; Yi Yang (IEEE Access)
With the aggravation of global ecological and environmental problems, coordinating the development of the relationship between natural resources and seeking sustainable social and economic development has become an important topic of concern to the scientific community today. Economic forecasting serves for economic decision-making, which is to improve the scientific level of economic management, reduce the blindness of economic decision-making and improve the correctness of decision-making. This article constructs the prediction model of urban circular economy development based on artificial neural network (ANN), and puts forward the innovation strategy of urban circular economy development path. Simulation results show that the response speed of this method is 21.55% higher than that of the comparison method, and the accuracy rate reaches 97.78%. Moreover, it has obvious advantages over the traditional algorithm in terms of error and recall rate. Compared with the actual economic data, the economic data predicted by the model is quite consistent, and the prediction of future data by the model basically accords with the development goal of the regional master plan. Therefore, it is feasible to use this method to analyze the development path of urban circular economy.