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PERFORMANCE INCREMENT OF HIGH SCHOOL STUDENTS USING ANN MODEL AND SA ALGORITHM

机译:基于ANN模型和SA算法的高中生绩效提升

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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.
机译:在这项研究中,人工神经网络(ANN)模型已用于学生的建模和设计?高中级别的成绩可以预测其成绩并提高其表现取决于四个因素:九年级的平均成绩,十年级的平均成绩,十一年级的平均成绩和每天的学习时间。为此,设计了一个神经网络。输入参数是第九阶段的平均成绩,第十阶段的平均成绩,第十一阶段的平均成绩和每天的平均学习时间。一个隐藏层被认为具有十个神经元。输出层是高中水平的平均成绩。考虑了一百个数据点来训练网络并计算权重。之后,通过模拟退火(SA)优化算法将ANN模型的结果用于最大化学生?高中等级。使用MATLAB软件完成实现部分。这项研究的主要目标是通过预测高中生来实现的?成绩,这可以帮助增加学生人数?在这一水平的教育表现。

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