[关键词]
[摘要]
创业板公司成立时间较短,企业规模较小,其研发投入的影响因素较多,本文利用营业净利率、每股收益、董监高年薪、可持续增长率、资产负债率、现金流量净额和GDP这些指标,运用径向基神经网络(RBF)和逆传播神经网络(BP)方法,构建了一个训练完成的神经网络模型,研究发现RBF神经网络模型比BP神经网络模型具有更好的拟合、预测效果。
[Key word]
[Abstract]
GEM enterprises are mostly setting up in a short time,having small business size and their performance is not outstanding,but most of them have a high growth. Their high growth performance are reflected in the ability of research and development on sensitive market reaction .However,there are many factors affecting R D investment. Based on the annual salary of the directors,supervisors and senior,sustainable growth,rate of assets and liabilities,net cash flow and GDP,using BP and RBF neural network model,we construct a neural network model which is training completed. It is found that the RBF neural network has better fitting and forecasting effect than BP neural network.
[中图分类号]
F230.9,F270
[基金项目]
云南省社科规划基金:云南省生态文明指数研究(201305),云南省社科规划教育科学基金:DEA视窗分析模型的云南省高校科研项目效率测度(AC15010),云南省教育厅基金:智力资本对云南企业贡献的测度研究(2014Y025)。 云南大学第四批中青年骨干教师资助基金(XT412003),云南大学人文社科青年项目:基于补贴和税收优惠的企业研发投入效应研究(13YNUHSS006),云南大学教学改革基金:管理类课程中案例研究评价体系的构建研究。