基于神经网络的产品突破性创新机遇识别

为了帮助企业在进行技术研发之前识别出最有潜力的技术，提高产品突破性创新的成功概率，提出了一种在模糊前端阶段进行突破性创新机遇识别的定量方法。首先，通过文献研究，确定产品突破性创新的路径特征，并提取产品突破性创新的相关影响因素，通过建立解释结构模型（ISM）提取并构建产品突破性创新机遇识别特征体系。其次，对突破性创新案例和非突破性创新案例进行特征对比，以各特征因素变化趋势为自变量，建立神经网络。最后，对样本数据进行拟合，构建产品突破性创新机遇识别模型。研究结果表明，研究所提模型能够对产品的突破性创新机遇进行有效识别，可应用于产品创新设计过程的模糊前端阶段。研究可为企业在突破性创新项目中更有效地进行机遇识别提供理论指导。

Opportunity recognition of product radical innovation based on neural networks

In order to help enterprises recognize the technology with the most potential before technology research and development and improve the success probability of product radical innovation,a quantitative method for recognizing radical innovation opportunities in the fuzzy front-end stage was proposed.Firstly,through literature research,the path characteristics of product radical innovation were determined,the relevant influencing factors of product radical innovation were extracted,and the characteristic system of product radical innovation opportunity recognition was extracted and constructed by establishing interpretive structure model (ISM).Then,the characteristics of radical innovation cases and non radical innovation cases were compared.Finally,taking the change trend of each characteristic factor as the independent variable,a neural network was established to fit the sample data,and a product radical innovation opportunity recognition model was constructed.The results show that the model can effectively recognize the radical innovation opportunities of products,and can be applied to the fuzzy front-end stage of product innovation design process to provide important guidance for enterprises to recognize opportunities more effectively in radical innovation projects.