计算机集成制造系统 ›› 2020, Vol. 26 ›› Issue (12): 3185-3194.DOI: 10.13196/j.cims.2020.12.001

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基于专利动态复杂网络的产业共性技术预测

吴颖文,纪杨建+,顾新建   

  1. 浙江大学机械工程学院浙江省先进制造技术重点研究实验室
  • 出版日期:2020-12-31 发布日期:2020-12-31
  • 基金资助:
    国家重点研发计划资助项目(2017YFB1400302)。

Industrial generic technology prediction based on dynamic complex network of patents

  • Online:2020-12-31 Published:2020-12-31
  • Supported by:
    Project supported by the National Key R&D Program,China(No.2017YFB1400302).

摘要: 共性技术选择作为优先组织和实施共性技术研发的基础,对产业战略升级和促进科技资源共享具有重要意义,由此提出产业共性技术预测方法以实现产业共性技术的高效选择。基于专利动态复杂网络,定义了共现广度和共现强度作为技术共性度的衡量指标,并根据这两个指标随时间的变化规律,运用多项式回归模型预测出未来的共性技术。以家电产业为例进行实证研究,验证了该预测方法的可行性。

关键词: 共性技术预测, 共现广度, 共现强度, 专利分析, 技术共现, 动态网络, 多项式回归模型

Abstract: As the basis of preferentially organizing and implementing generic technology research and development,the selection of generic technology is of great significance to upgrade industrial strategy and enhance national core competitiveness.Therefore,the prediction method of industrial generic technology was proposed to realize the efficient selection of industrial generic technology.Based on the technology co-occurrence dynamic network of patents,co-occurrence breadth and co-occurrence strength were defined as indicators of the degree of technology commonality.According to the change rule of these two indicators over time,the polynomial regression model was used to predict the future industrial generic technology.The household appliance industry was chosen as the case,and the empirical study verifies the feasibility of the proposed method.

Key words: generic technology prediction, co-occurrence breadth, co-occurrence strength, patent analysis, technology co-occurrence, dynamic network, polynomial regression model

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