Abstract: On the basis of study on the low level of innovation efficiency and conversion rate, the index system of synergy innovation platform is put forward inspired by the mechanisation of synergy innovation. The index system is composed of five aspects of organization coordination，resource integration，knowledge sharing,achievement transformation and risk scattering. Based on the data of 14 industrial technology research institutes from all over the country, The Analytic Hierarchy Process is exploited to calculate weight of indicators,and simulation experiments are proceeded with BP Neural Network. Thus, the thesis proposes some policy recommendations to increase efficiency and reliability of synergy innovation.

摘要： 针对工业技术研究院创新效率和成果转化率低下等问题，在探索协同创新作用机理的基础上，提出了涵盖组织协作、资源整合、知识分享、成果转化、风险分担等维度的工研院协同创新平台评价指标体系。借助层次分析法对指标体系及其权重系数进行了测算，并利用三层BP神经网络模型开展了模拟仿真，以分布于全国范围的14家工研院的数据对所构建的协同创新平台评价指标体系及其权重系数的有效性与可靠性进行了验证，提出了帮助工研院提高创新效益的政策建议，为政府科技主管部门进一步完善国家创新体系提供管理参考。