Research on the Course Structure of Mechanical Engineering Using Neural Network

Yang YANG, Hong WANG, Cai-hong YU, Cheng-cheng HUA, Chang-hao YIN, Kai-yuan LI

Abstract


Mechanical engineering course system was taken as the research object, based on QS World University rankings relevant parameters, in order to cultivate innovative talents, used modern mathematical analysis method, established a three layer BP neural network analysis model, errors have been lumped in -0.6~+0.5. Based on this model, some Chinese universities, which were not listed in the QS rankings system, were quantitatively calculated. The results of comparative analysis show that the structure of the mechanical course system in universities is an important influence factor to the rankings of the QS system. This study is useful for the mechanical engineering disciplines to enter the international first-class disciplines and cultivate innovative talents.

Keywords


First class discipline, Course structure, Neural network, Innovative talents


DOI
10.12783/dtssehs/aetms2017/15832

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