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Predicting on Scale Development of Higher Education Based on LM and ANN

机译:基于LM和ANN的高等教育规模发展预测

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The paper employs Granger causality test to analyze the inner relationships among factors that attribute to the scale development of higher education, and builds an Artificial Neural Network (ANN) and a Logistic Model (LM) to forecast the total demand and supply of the scale development of higher education in the process of urbanization in Jiangxi province. The results show: Firstly, the Granger causality test reveals that the key parameters that impact the scale development of higher education are the per capita GDP and the urbanization rate. Secondly, the elasticity analysis of demand to supply of the scale development of higher education reveals the development of higher education in Jiangxi province is entering the stage with E1 when the critical point E1 passed after 1999. Therefore, its development of higher education should be paid more attention to the quality, and the scale that is quickly expanding should be appropriately controlled.
机译:本文采用Granger因果关系测试,分析了归因于高等教育规模发展的因素之间的内部关系,并建立一个人工神经网络(ANN)和物流模型(LM),以预测规模发展的总需求和供应高等教育在江西省城市化进程中。结果表明:首先,格兰杰因果试验表明,影响高等教育规模发展的关键参数是人均GDP和城市化率。其次,对高等教育规模发展的需求需求的弹性分析揭示了江西省高等教育的发展正在与e <1进入阶段,当临界点E> 1通过1999年后。因此,它的发展更高应更加关注质量的教育,并且应适当控制快速扩展的规模。

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