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  • 标题:PREDICTING THE SUCCESS RATES OF SCHOOLS USING ARTIFICIAL NEURAL NETWORK
  • 本地全文:下载
  • 作者:AHMED SUBHI ABDALKAFOR ; AIMAN MAJID NASSAR ; MUSTAFA NADHIM OWAID
  • 期刊名称:Journal of Theoretical and Applied Information Technology
  • 印刷版ISSN:1992-8645
  • 电子版ISSN:1817-3195
  • 出版年度:2018
  • 卷号:96
  • 期号:19
  • 出版社:Journal of Theoretical and Applied
  • 摘要:The Prediction is one of the most important and prevalent topics recently. It is an estimation of what will occur in the future depending on the data obtained previously. In this paper, a model was proposed to predict the success rates of schools neural networks approach. The proposed model was trained and tested by taking the data from General Directorate of Education in Anbar for the academic year 2016-2017 then divided into two equal groups (male and female). Physics and Chemistry subjects are considered the main influent on the success rate after applying the Garson technique. It was obtained a real equation that can be used to predict future success rates for all other educational institutions with regression for Training, Validation and Testing reached to 95.161%.
  • 关键词:Artificial neural network; Prediction; Success Rate; Regression
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