## 2 Literature Review
### Research on the Evaluation of High-Tech Zones  
Many scholars have studied the evaluation of high-tech zones. For example, based on the qualitative analysis of science and technology parks, [PERSON] and [PERSON] [22] conducted quantitative research on science and technology parks through index decomposition. [PERSON] [23] analyzed the promotion of innovation by high-tech parks using the example of Moglino, Russia. [PERSON] et al. [24] assessed science parks' performance based on an analysis of selected Italian parks and found the important role of environment context, the stakeholder's commitment, and the life cycle of the science park. [PERSON] et al. [25] applied a fuzzy expert system to the evaluation of science and technology parks. [PERSON] et al. [26] provided a theoretical framework of national science park's evaluation and applied it to the Italian and Spanish systems. In China, there are several influential evaluation systems of national high-tech zones formulated by the government. For example, the evaluation system laid down by the Ministry of Science and Technology reveals the comprehensive innovation abilities of all the national high-tech zones. \"Zhongguancun Index\" and \"Zhangjiang Index\" evaluate the two tech zones' innovation ability, respectively. Chinese scholars have also conducted a large amount of work in evaluating high-tech zones. For example, [PERSON] et al. [27] established an evaluation system for high-tech zone competitiveness from four dimensions: technological innovation, capital support, entrepreneurial environment, and development performance. [PERSON] [28] established an evaluation system for the technological innovation capacity of high-tech zones, which includes 16 indicators, such as total assets, R&D expenses, and R&D personnel, through a comprehensive study of technological innovation processes and the use of expert methods and discriminant analysis. [PERSON] and [PERSON] [29], starting from economic transformation, constructed an evaluation system for innovation transformation indicators from four perspectives: industrial clusters, innovation input, innovation output, and innovation environment. [PERSON] et al. [30] constructed an indicator system for the high-quality development level of national high-tech zones. They used the entropy method to measure the high-quality development level of national high-tech zones in China from 2013 to 2018. However, there is limited research on the evaluation system for China's world-class high-tech zones. A search on CNKI (China National Knowledge Infrastructure) yielded only two relevant articles. [PERSON] [31] used principal component analysis and SPSS17.0 to evaluate the capital supply and demand capacity of six national autonomous innovation demonstration zones striving to become world class. [PERSON] [32] systematically reviewed the development theories and evaluation indicators of high-tech parks both domestically and internationally. They proposed a comprehensive evaluation indicator system for world-class parks based on the balanced scorecard. They partially applied it to the empirical investigation of creating a world-class park in Suzhou Industrial Park, identified problems, and provided recommendations. According to statistics and analysis, there are over 10 methods used in the construction of evaluation systems for high-tech zones. Commonly used methods include the analytic hierarchy process (AHP), expert scoring, factor analysis, multi-level grey evaluation, and data envelopment analysis (DEA). In recent years, with the development of machine learning algorithms, some scholars have applied machine learning in evaluations. For example, [PERSON] [9] used the Random Forest method to construct a risk indicator system for real estate projects and verified the correctness of the Random Forest algorithm in the real estate project risk evaluation model.