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PDF(1881 KB)
基于专利挖掘的绿色发展技术主题分析与趋势研究
Research on Topic Analysis and Trends of Green Development Technologies Based on Patent Mining
[目的/意义] 旨在明确绿色发展关键技术领域，预测技术演变趋势，为技术创新、政策制定及可持续发展提供科学依据。[方法/过程] 以patsnap专利数据库中的相关数据为样本来源，运用TF-IDF、LDA主题模型及困惑度分析探索主题词分布并提取主题，同时进行语义网络主题聚类，实现技术关联分析，综合分析其现状与趋势。[结果/结论] 研究表明，绿色发展技术目前处于成熟初期；专利主题可归纳为绿色生产技术、绿色建筑施工技术、电机驱动技术等7类；发展方向将从单一技术向系统集成、从资源高效利用向循环经济、从传统能源向可再生能源，以及从单一环境治理向综合生态管理全面转型。从系统的角度分析绿色发展技术的现状，并探究其发展趋势，为该领域相关技术的发展提供借鉴。
[Purpose/Significance] To identify key technological areas for green development, predict technology evolution trends, and provide a scientific basis for technological innovation, policy formulation, and sustainable development. [Method/Process] Data from the patsnap patent database was used as the sample source. Techniques such as TF-IDF, LDA topic modeling, and perplexity were applied to explore the distribution of topic terms and extract key themes. Additionally, semantic network topic clustering was conducted to achieve technological association analysis, comprehensively analyzing the current status and trends within the patent data. [Results/Conclusion] The research reveals that green development technology is in the early stages of maturity. Patent topics can be classified into seven categories: green production technology, green building construction technology, motor drive technology, etc. The development direction involves a comprehensive transformation from single technologies to system integration, from resource-efficient utilization to circular economy, from traditional energy to renewable energy, and from single environmental governance to integrated ecological management. By analyzing the current status of green development technology from a systematic perspective and exploring its development trends, this article provides valuable insights for the advancement of related technologies in this field.
green development / patent mining / Latent Dirichlet Allocation(LDA) topic model / future prospect
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