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Student Performance Prediction Model Based on Lion-Wolf Neural Network


Ramanathan L1*,Angelina Geetha2,Khalid M3,Swarnalatha P4


1School of Computer Science & Engineering, VIT University, Vellore, Tamilnadu, India.
2 Department of CSE, B.S. Abdur Rahman University, Chennai, Tamilnadu, India
3Director, NITMAS & TNU, Kolkata, India
4School of Computer Science & Engineering, VIT University, Vellore, TamilNadu, India


Early prediction of student performance helps to take action for better achievements of students. To achieve the better education standard, several attempts have been made to predict the performance of the student, but the prediction accuracy is not acceptable. To accomplish the enhanced prediction, neural network (NN) based method is proposed. In this paper, an approach to predict student academic performance in college education based on Lion-Wolf artificial neural network is proposed. Lion algorithm and Grey Wolf optimizer is integrated to develop a Lion-wolf training algorithm to find the optimal weight for every neuron in NN. The proposed prediction model is validated based on Mean Squared Error (MSE) & Root Mean Square Error (RMSE) with the existing NN based prediction model. The experimental results show that performance of proposed prediction model is improved compared to existing prediction model with MSE of 5.25 and RMSE of 2.3.


Educational data mining, Lion optimization, Grey wolf optimizer, Prediction model, Entropy measure.

Full Text:

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