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Academic Journal of Computing & Information Science, 2019, 2(3); doi: 10.25236/AJCIS.020301.

Evaluation of Scientific Research Ability in Colleges and Universities Based on Discrete Hopfield Neural Network

Author(s)

Qimeng Tao

Corresponding Author:
Qimeng Tao
Affiliation(s)

Science & Technology College, North China Electric Power University, Baoding, Hebei, 071003, China

Abstract

With the development of China's economy and the continuous enhancement of its comprehensive strength, the development of China's higher education has entered the upper-middle level of the world, but the development of education in China is not balanced.Taking Jiangsu Province as an example, this paper gives a comprehensive evaluation of the quality of undergraduate education in 13 prefecture-level cities in Jiangsu Province.This paper firstly reviews the data of relevant indicators given in the paper, and considers the impact of a small number of indicators that cannot be accurately quantified. Combined with the associative memory ability of discrete Hopfield neural networks, an evaluation model of discrete Hopfield undergraduate education quality is established.Secondly, the university is divided into five grades and the average value of each index is used as the ideal evaluation index of each grade, which is the balance point of Hopfield neural network.Finally, the results of the simulation of the example are obtained by using the neural network toolbox that comes with Matlab.

Keywords

Discrete Hopfield neural network evaluation of scientific research ability

Cite This Paper

Qimeng Tao. Evaluation of Scientific Research Ability in Colleges and Universities Based on Discrete Hopfield Neural Network. Academic Journal of Computing & Information Science (2019), Vol. 2, Issue 3: 1-8. https://doi.org/10.25236/AJCIS.020301.

References

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