The Evaluation of College Students’ Comprehensive Quality Based on Rough and ANN Methods

  • Xiaofeng Li
  • Lingyuan Liu
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 241)


The risk measure for enterprise technology innovation is a hotspot problem and the forward position of enterprise management, is a much subject overlapping edge research program, it is very difficult to research this problem. In this paper, based on Rough set theory and ANN method, Rough-ANN model for dynamic risk measure of enterprise technological innovation is established. It takes the advantages of the informational reduction principle of rough set theories and ANN predominance which has stronger concurrent processing, approach advantage and sort study capability. Thus the model may simulate the mankind’s abstracting logic thinking and image intuitive thought to measure enterprise technological innovation risk. This model can identify the main attributes of technological innovation risk, reduce the information accumulate cost of risk measure, improve the efficiency of risk measure, make the sophisticated problem of technological innovation risk measure simplified. Therefore, this model has better practice operability. Theoretical analysis and experimental results show the feasibility and validity of the model. The research work supplies a new way for dynamic risk measure for technological innovation.


Comprehensive quality Evaluation Rough set BP artificial neural network 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  1. 1.School of BusinessSichuan UniversityChengduPeople’s Republic of China

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