Proceedings of the 2018 International Conference on Transportation & Logistics, Information & Communication, Smart City (TLICSC 2018)

Application of BP Network based on GA in Student Evaluation

Authors
Shixin Li, Hai Zhang, Kaixin Li, Chaonan Fan
Corresponding Author
Shixin Li
Available Online December 2018.
DOI
https://doi.org/10.2991/tlicsc-18.2018.2How to use a DOI?
Keywords
Student examination evaluation, the BP neural network optimized by GA, Data mining technology.
Abstract
The examination evaluation of students is a complex, multi factor, multi variable nonlinear system. The traditional evaluation method is difficult and fair to reflect the students' learning effect. In this paper, the student examination evaluation system model based on the BP neural network based on GA is set up, the student sample results are collected according to the index, data mining technology is used for learning and training, and the trained model is applied to performance prediction. The simulation results show that the prediction accuracy of the student test evaluation model of the BP neural network optimized by GA is far more than the simple BP network prediction model and can overcome the interference of various subjective factors to the students' performance.
Open Access
This is an open access article distributed under the CC BY-NC license.

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Proceedings
2018 International Conference on Transportation & Logistics, Information & Communication, Smart City (TLICSC 2018)
Part of series
Advances in Intelligent Systems Research
Publication Date
December 2018
ISBN
978-94-6252-621-1
ISSN
1951-6851
DOI
https://doi.org/10.2991/tlicsc-18.2018.2How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Shixin Li
AU  - Hai Zhang
AU  - Kaixin Li
AU  - Chaonan Fan
PY  - 2018/12
DA  - 2018/12
TI  - Application of BP Network based on GA in Student Evaluation
BT  - 2018 International Conference on Transportation & Logistics, Information & Communication, Smart City (TLICSC 2018)
PB  - Atlantis Press
SN  - 1951-6851
UR  - https://doi.org/10.2991/tlicsc-18.2018.2
DO  - https://doi.org/10.2991/tlicsc-18.2018.2
ID  - Li2018/12
ER  -