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A New Method for Prediction of School Dropout Risk Group Using Neural Network Fuzzy ARTMAP

机译:使用神经网络模糊艺术图预测学校辍学风险组的新方法

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Dropping out of school is one of the most complex and crucial problems in education, causing social, economic, political, academic and financial losses. In order to contribute to solve the situation, this paper presents the potentials of an intelligent, robust and innovative system, developed for the prediction of risk groups of student dropout, using a Fuzzy-ARTMAP Neural Network, one of the techniques of artificial intelligence, with possibility of continued learning. This study was conducted under the Federal Institute of Education, Science and Technology of Mato Grosso, with students of the Colleges of Technology in Automation and Industrial Control, Control Works, Internet Systems, Computer Networks and Executive Secretary. The results showed that the proposed system is satisfactory, with global accuracy superior to 76% and significant degree of reliability, making possible the early identification, even in the first term of the course, the group of students likely to drop out.
机译:从学校辍学是教育中最复杂,最重要的问题之一,造成社会,经济,政治,学术和财务损失。 为了促进解决局势,本文介绍了智能,强大,创新系统的潜力,为学生辍学的风险群体预测,使用模糊艺术神经网络,这是人工智能的技术之一, 有可能继续学习。 本研究是根据Mato Grosso的联邦教育学院,科技学院进行的,与自动化和工业控制,控制工程,互联网系统,计算机网络和执行秘书学生的学生。 结果表明,建议的系统令人满意,全球精度优于76%和显着程度的可靠性,使得即使在课程的第一个术语中也可能辍学。

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