摘要
构建基于多层前馈神经网络的仿真模型,以台湾16年面板数据进行训练,并将训练得出的模式有条件移植至福建,给出提升福建科技服务水平的建议。训练模型表明,当政府提高集聚要求时,研发经费及基础研究经费的增加最为重要;移植模型认为,福建省应增加研发经费投入、提高基础研究经费比率、促进企业增加研发经费、培养激励研究人员,以此促进产业集聚。
A simulation model is build based on multi-layer feed forward neural networks with a 16-year panel data trained, and suggestions on Fujian technology services are given according to the conditional transplanting to Fujian. Training model shows that, improving the R＆D funding and the funding for basic research are important when the industrial gathering are required ; transplantation model to Fujian Province indicates that,there are four ways for government to promote the gath- ering of the industry：improving the R＆D funding,increasing the ratio of basic research funding, encouraging enterprises to increase R＆D funding and motivating the researchers.
出处
《科技进步与对策》
CSSCI
北大核心
2014年第3期42-49,共8页
Science & Technology Progress and Policy
基金
福建省软科学基金项目(2011R0091)
关键词
科技服务
产业集聚
神经网络
移植模型
训练模型
Science and Technology Services
Industrial Agglomeration
Neural Network
Transplantation Model
Training Model
