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With the development of global economy, the evaluation of industrial clusters has become an important method to scientifically analyze the advantages and disadvantages of industrial development. The current research model uses the traditional evaluation method, which leads to the problem of unsatisfactory evaluation results and low effect. This paper proposes an evaluation model based on the BP neural network combined with the LM algorithm, which has the advantages of fast convergence speed and strong application ability. The comprehensive evaluation model of industrial clusters is put forward from the comprehensive application of the scale, benefit, and 27 related evaluation indexes of industrial clusters. This paper takes Beijing, Tianjin, and Hebei industrial clusters for BP-LM evaluation and analysis, which fully illustrates the advantages of this method. The evaluation results show that the evaluation target value and the average error of the overall parity have obvious advantages compared with those of other models, which provides application guidance for local economic development and policy formulation. [ABSTRACT FROM AUTHOR]

Based on the PSR conceptual evaluation model of urban green and low-carbon development competitiveness, this paper evaluates the green and low-carbon development competitiveness of 13 cities in Beijing-Tianjin-Hebei from 2010 to 2019 and reveals their spatial effects and obstacle factors combined with the spatial autocorrelation and obstacle model. The results show the following: (1) In terms of the overall situation, the evaluation index of urban green and low-carbon development competitiveness in the Beijing-Tianjin-Hebei region shows a fluctuating upward trend as a whole from 2010 to 2019. Among them, the comprehensive evaluation indexes of Beijing, Zhangjiakou, and Tianjin are very competitive, while Hengshui, Handan, and Xingtai are relatively weak. (2) In terms of spatial data analysis, the global and local Moran's I of Beijing-Tianjin-Hebei cities from 2010 to 2019 were positive and passed the 1% significant level test. This shows that the comprehensive evaluation index of urban green low-carbon development competitiveness of Beijing-Tianjin-Hebei cities has a positive spatial correlation, and the spatial agglomeration effect is significant. On the whole, it presents a spatial agglomeration pattern of "high in the north, partial jump, and low in the south". (3) In the aspect of obstacle factor analysis, the proportion of the tertiary industry output value in GDP, energy consumption of ten thousand yuan of GDP, the urban green technology innovation level, and industrial soot emission of ten thousand yuan of GDP are the main obstacle factors restricting the improvement of urban green low-carbon development competitiveness in Beijing-Tianjin-Hebei cities. [ABSTRACT FROM AUTHOR]