Implementing green development is important to realizing a harmonious relationship between humans and nature, and has attracted the attention of governments all over the world. This paper uses the PMC (Policy Modeling Consistency) model to make a quantitative evaluation of 21 representative green development policies issued by the Chinese government. The research finds: firstly, the overall evaluation grade of green development is good and the average PMC index of China’s 21 green development policies is 6.59. Second, the evaluation of 21 green development policies can be divided into four different grades. Most grades of the 21 policies are excellent and good; the values of five first-level indicators about policy nature, policy function, content evaluation, social welfare, and policy object are high, which indicates that the 21 green development policies in this paper are relatively comprehensive and complete. Third, most green development policies are feasible. In twenty-one green development policies, there are: one perfect-grade policy, eight excellent-grade policies, ten good-grade policies, and two bad-grade policies. Fourthly, this paper analyzes the advantages and disadvantages of policies in different evaluation grades by drawing four PMC surface graphs. Finally, based on the research findings, this paper puts forward suggestions to optimize the green development policy-making of China.

Green development is the background of common prosperity and is important for the sustainable development of China. The purpose of this paper is to quantitatively evaluate China’s common prosperity policies to understand the advantages and disadvantages of common prosperity policies. In this paper, 15 representative common prosperity policies are research subjects, and this study uses the PMC (Policy Modeling Consistency) index method to assess the quality of common prosperity policies in China. This study, firstly, finds that the average value of the 15 common prosperity policies is 6.47, evaluated as a good grade. Secondly, 80% of policies are evaluated as a good or excellent grade, which means that the quality of the policy making of 80% of policies is at least good. Except for policy prescription, policy subject and policy incentive, the values of other first-level indicators are all greater than six, indicating that the Chinese government’s formulation level of common prosperity policies is relatively high. Thirdly, among fifteen common prosperity policies, one policy is evaluated as a perfect grade (quality of policy making is very good), four policies are evaluated as excellent (quality of policy making is better than required), eight policies are evaluated as good (quality of policy making is good) and two policies are evaluated as bad (quality of policy making is bad). Fourthly, by drawing figures composed of PMC curves, this paper analyzes common prosperity policies of different grades. Finally, some suggestions are proposed in this study to improve China’s common prosperity policies.

Green development and common prosperity are two major development goals put forward by the Chinese government. Based on the background of green development, the index system of common prosperity is designed in this paper, and the entropy method and coefficient of variation method are used to calculate the level of common prosperity in China from 2010 to 2020. The research findings are as follows: Firstly, the level of common prosperity based on the background of China’s green development has been raised from 2010 to 2020. The level of common prosperity based on the background of China’s green development has increased from 0.301 in 2010 to 0.513 in 2020. Secondly, based on the background of China’s green development, the level of common prosperity in the eastern region is higher than that in the northeast region, the northeast region is higher than that in the central region, and the central region is higher than that in the western region. Thirdly, the regional difference in common prosperity level based on the background of green development shows a trend of narrowing, with the coefficient of variation decreasing from 0.25 in 2010 to 0.13 in 2020. Finally, based on the research findings, corresponding suggestions are put forward to promote common prosperity.

Evaluating the level of green development is of great significance to better implement the concept of green development. By constructing an evaluation index system for green development, this paper comprehensively uses the entropy weight Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) method and coefficient of variation method to evaluate the green development level of 30 provinces in China from 2010 to 2019 and analyzes the regional differences of green development in China. The research findings are as follows: First, the level of green development in China is low but shows a slow rise trend, from 2010 to 2019; China’s green development level rises from 0.274 to 0.317, an increase of 15.7%. Secondly, regional differences of green development in China are obvious, with the level ranking from high to low as eastern, western, and central regions. Third, regional differences in China’s green development first widen and then narrow, with the variation coefficient of green development in 30 provinces and eastern, central, and western regions of China showing an inverted U-shaped trend of first increasing and then decreasing. Fourth, the regional difference of green development in eastern China is largest, followed by western China, and the smallest is central China. Finally, based on research findings, relevant policy recommendations are put forward.

The sustainable economic learning course recommendation can quickly find the knowledge information that the user really needs from the massive information space and realize the personalized recommendation to the user. However, the occurrence of trust attacks seriously affects the normal recommendation function of the recommendation system, resulting in its failure to provide users with reliable and reliable recommendation results. In order to solve the vulnerability of the recommendation system to the support attack, based on text vector model and support vector machine, this paper makes a comprehensive analysis of the current research status of the robust recommendation technology. Moreover, based on the idea of suspicious user metrics, this paper has conducts in-depth research on how to design highly robust recommendation algorithms, and constructs a highly reliable sustainable economic learning course recommendation model. In addition to this, this research tests the performance of the system from two perspectives of course recommendation satisfaction and system retrieval accuracy. The experiment proves that the model constructed in this paper performs well in the recommendation of sustainable economic learning courses.