基于GBDT算法的装备制造产业技术创新力研究  

DResearch on the Technology Innovation Capacity of Equipment Manufacturing Industry Based on GBDT Algorithm

作　　者：乐思诗[1] 叶斌 LE Si-shi;YE Bin(Library,Ningbo Polytechnic,Ningbo 315800,China;School of Economics and Management,Zhejiang University of Science and Technology,Hangzhou 310023,China)

机构地区：[1]宁波职业技术学院图书馆,浙江宁波315800 [2]浙江科技学院经济与管理学院,浙江杭州310023

出　　处：《科技创新与生产力》2023年第3期102-104,共3页Sci-tech Innovation and Productivity

基　　金：浙江省哲学社会科学规划课题(20NDJC334YBM;20NDQN308YB)。

摘　　要：本文将机器学习方法应用于装备制造业技术创新分析,基于GBDT算法分析制约其技术创新的因素,通过城市、行业两个变量得出R&D人员投入、R&D经费内部支出和技术改造经费支出是制约各个城市装备制造业发展的因素。汽车制造业比其他细分行业对装备制造业技术创新影响更大。受制于消化吸收能力,技术改造的影响在投入前期并不稳定。This paper applies machine learning methods to the analysis of technological innovation in the equipment manufacturing industry.Based on the GBDT algorithm,the factors that constrain technological innovation in the equipment manufacturing industry are analyzed.Through two variables of city and industry,it is concluded that R&D personnel investment,R&D internal expenditure,and technological transformation expenditure are the factors that constrain the development of the equipment manufacturing industry in various cities.In addition,compared to other segmented industries,the automobile manufacturing industry has a greater impact on technological innovation in the equipment manufacturing industry.Due to the limitation of digestion and absorption capacity,the impact of technological transformation is not stable in the early stage of investment.

关 键 词：装备制造业 技术创新 机器学习 梯度提升法 

分 类 号：F273.1[经济管理—企业管理] F426[经济管理—国民经济]