Research and Application on the Research Innovation Ability of the Graduate Student Based on the Fuzzy Neural Network

Abstract:

During the course of building an innovative country and enhancing the independent innovation capability, universities are the main force and the important source of high-tech innovation. The evaluation on the university's innovation ability, not only may improve university's efficiency and level of scientific research, but also make a significant sense to perfect the china' scientific research innovation system. Based on Referring to the recent research achievements at home and abroad, research and design work was carried out in the following area. Firstly, the multi-university research innovation ability evaluating indicator system is designed in this paper. By the principle of science and justice, through questionnaires, expert opinion and reference to relevant research results. The paper designed the multi-university's research innovation ability evaluating indicator system. A variety of typical evaluation models and methods are studied. Then two evaluation models between PCA-BP and PCA-FNN are taken into comparison. And the results show that the research and application of PCA-FNN is proved to be a new method and made a significant attempt for the university’s evaluation of research innovation ability.

• Periodical: Applied Mechanics and Materials (Volumes 687-691)
• Pages: 2909-2912
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.687-691.2909
• Online since: November 2014
• Authors: Liang Hu*, Gan Lan Yan, Long Li
• Keywords: BP Neural Network (BPNN), Fuzzy Neural Network, Principal Component Analysis (PCA), Scientific Research Evaluation

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