Fuzzy Neural Network-Based Performance Evaluation For Patent Technology Transformation Of Scientific Research Institutes

Patent technology transformation is an important way for patent technology to realize the transition, commercialization and industrialization. Scientific research institutes, as an important development body of patent technology, plays a very important role in the transformation process. How to effectively evaluate patent technology transformation performance level of scientific research institutes, how to improve the level of patent technology transformation through the evaluation, become a major focus of this study. Therefore, this article choose patent technology transformation of scientific research institutes as a breakthrough point, to explore the evaluation methodology of the patent technology transformation performance of scientific research institutes, to find the countermeasure to promote the patent technology transformation performance level of scientific research institutes.This paper firstly analyses present situation of domestic and foreign related research, especially the development and the influence factors of patent technology transformation of our country’s scientific research institutes. Secondly building an index system for performance evaluation of patent technology transformation and a fuzzy neural network evaluation model, which lays the foundation for the building of evaluation method; Then using three evaluation method, multilevel grey evaluation method, fuzzy comprehensive evaluation method and fuzzy neural network method, to evaluate the same empirical case, to explore the superiority of the fuzzy neural network performance evaluation method; Finally puts forward the measures to enhance the performance level of patent technology transformation, hope to provides methods and theoretical support for promoting patent technology transformation performance of scientific research institutes.