Performance increment of high school students using ANN model and SA algorithm
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In this study, Artificial Neural Network (ANN) model has been used for modeling and design of students’ grades in high school level to predict their grades and increase their performance depends on four factors: grades average of ninth level, grades average of tenth level, grades average of eleventh level, and the average of studying hours per day. To do so a Neural Network has been designed. The input parameters were the grades average of ninth stage, grades average of tenth stage, grades average of eleventh stage, and average studying hours per day. One hidden layer was considered with ten neurons. The output layer is Grades average of high school level. One hundred data points were considered to train the network and calculate the weights. After that, the results of ANN model have been used by Simulated Annealing (SA) optimization algorithm to maximize the students’ grades in high school level. MATLAB software was used to do the implementation part. The main goal of this study has been achieved by predicting high school students’ grades, which can help in increasing the students’ performance in this level of education.
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