Predicting Student Academic Performance: A Comparison of Two Meta-Heuristic Algorithms Inspired by Cuckoo Birds for Training Neural Networks

@article{Chen2014PredictingSA,
  title={Predicting Student Academic Performance: A Comparison of Two Meta-Heuristic Algorithms Inspired by Cuckoo Birds for Training Neural Networks},
  author={Jeng-Fung Chen and Ho-Nien Hsieh and Quang Hung Do},
  journal={Algorithms},
  year={2014},
  volume={7},
  pages={538-553}
}
Predicting student academic performance with a high accuracy facilitates admission decisions and enhances educational services at educational institutions. This raises the need to propose a model that predicts student performance, based on the results of standardized exams, including university entrance exams, high school graduation exams, and other influential factors. In this study, an approach to the problem based on the artificial neural network (ANN) with the two meta-heuristic algorithms… CONTINUE READING

References

Publications referenced by this paper.
Showing 1-10 of 33 references

Cuckoo Search and Firefly Algorithm: Theory and Applications

  • X. S. Yang
  • 2014
1 Excerpt

Comment on Cuckoo search: A new nature-inspired optimization method for phase equilibrium calculations

  • S. Walton, M. R. Brown, O. Hassan, K. Morgan
  • Fluid Phase Equilib
  • 2013
2 Excerpts

Parameter Optimization via Cuckoo Optimization Algorithm of Fuzzy Controller for Liquid Level Control

  • S. Balochian, E. Ebrahimi
  • 2013
1 Excerpt

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