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Evaluation of Students` Learning Based on Cybernetic Models with Differential Equations of Fractional Order

机译:基于网络学模型的学生课程评估分数序列微分方程

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In this paper, the implementation of a cybernetic learning model based on differential equations of fractional order is justified. Experimental learning results were obtained by testing students during the academic semester. Based on a heterogeneous differential equation with integer order, learning graphs have been compared to a family of models with fractional order equations. Consequently, fractional-order equations are proved to have better approximation properties. Criteria for assessing the learning and differentiation of teaching methods based on the parameters of fractional order equations are proposed.
机译:在本文中,基于分数顺序的微分方程的网络感受学习模型的实现是合理的。 通过在学术学期期间测试学生获得了实验学习结果。 基于具有整数顺序的异构微分方程,已经将学习图与具有分数级方程的模型系列进行了比较。 因此,证明了分数级方程具有更好的近似特性。 提出了基于分数级方程参数评估教学方法学习和分化的标准。

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