Evaluation of industrial intelligence and evaluation of the effect of circular economy development: Inter‐provincial data from 2012 to 2022

Abstract

AbstractAs artificial intelligence and automation technology develop, the concept and application of intelligent manufacturing is recognized by more and more people, and the development trend of industrial enterprises' intelligence is gradually remarkable. In order to improve the industrial intelligence of an economy and indirectly promote its circular economy, this study uses fuzzy hierarchical analysis and feed‐forward neural network algorithm to construct an evaluation model of the intelligence of an economy and multiple linear regression to build an analytical model to evaluate the effect and impact of industrial intelligence on circular economy. Based on China's provincial economic yearbooks from 2012 to 2022, the total absolute difference between the average absolute error values of the hybrid fuzzy hierarchical analysis and feedforward neural network algorithm model, the traditional hierarchical analysis model and the manual evaluation method designed in this study are 0.14 and 0.31, respectively. In the industrial intelligentization ‐ industrial structure model, except for the proportion of output value of state‐owned enterprises above the scale, all other indicators have a significant positive effect, indicating that industrial intelligence, information construction and urbanization are conducive to economic scale growth. In the industrial intelligentization ‐ environmental bias technology progress model, the regression coefficients of the proportion of output value of state‐owned enterprises above the scale, industrial intelligence score, and postal communication per capita are 3.846, 0.8510, and 0.0381, respectively, which can accelerate the industrial transformation of the economy. In the industrial intelligence‐economic scale model, the percentage of output value of state‐owned enterprises above the scale significantly effects the environmental bias toward technological progress and the regression coefficient is −34.72, indicating that the lower percentage of state‐owned enterprises in the economic structure is more conducive to industrial intelligence. This study has some reference significance for auxiliary economies to carry out industrial intelligence and stimulate the development of circular economy.