doi: 10.18178/ijiet.2019.9.2.1186
A Neural Network Based Approach for Exhibition Evaluation in Modern Science and Technology Museums
Qiusha Min
,
Yating Chen ,
Zhifeng Wang ,
Dan Xia ,
Mingzhang Zuo ,
Junming Ye
Abstract
The Modern Science and Technology Museum is an important place for popularizing scientific knowledge and improving the scientific quality of the public, playing an important role in promoting scientific and technological progress. This paper presents a quantified evaluation method for exhibits in Science and Technology Museums. This method establishes a three-level index system and trains the weight of each index in the index system through neural network to evaluate exhibits quantitatively. Compared with traditional evaluation methods, this method can more comprehensively and scientifically evaluate the display effect of exhibits. Through this evaluation index system, administrator of Science and Technology Museum can know what aspects of the exhibit need to be improved. In response to these aspects, the exhibit is modified to improve its display effect.
Keywords
- Modern science and technology museum
- exhibits
- evaluation
- neural network
How to Cite
Qiusha Min, Yating Chen, Zhifeng Wang, Dan Xia, Mingzhang Zuo, and Junming Ye, "A Neural Network Based Approach for Exhibition Evaluation in Modern Science and Technology Museums," International Journal of Information and Education Technology, vol. 9, no. 2, pp. 123-128, 2019. https://doi.org/10.18178/ijiet.2019.9.2.1186
Copyright & License
Copyright © 2019 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).