AUTHOR=Zhou Rui , He Zhihua , Lu Xiaobiao , Gao Ying 

TITLE=Applying Deep Learning in the Training of Communication Design Talents Under University-Industrial Research Collaboration

JOURNAL=Frontiers in Psychology

VOLUME=Volume 12 - 2021

YEAR=2021

URL=https://www.frontiersin.org/journals/psychology/articles/10.3389/fpsyg.2021.742172

DOI=10.3389/fpsyg.2021.742172

ISSN=1664-1078

ABSTRACT=The purpose of the study is to solve the problem of the mismatching between the supply and demand of the talents that universities provide for society, whose major is communication design. The correlations between social post demand and university cultivation, and between social post demand and the demand indexes of enterprises for posts are explored under the guidance of IUR (Industry-University-Research). The BPNN (Back Propagation Neural Network) is used, and the advantages of SARIMA (Seasonal Autoregressive Integrated Moving Average model) model is combined to design the SARIMA-BP (Seasonal Autoregressive Integrated Moving Average model, back propagation neural network) model after the relevant parameters are adjusted. Through experimental analysis, it is found that the error of the root mean square of the designed SARIMA-BP model in post prediction is 7.523, and that of the BP neural network model is 16.122. The effect of the prediction model designed based on deep learning is smaller than that of the previous model based on the neural network, and it can predict future posts more accurately for colleges and universities. Guided by “University-Industrial Research Collaboration”, students will have more practice in the teaching process in response to the social needs. “University-Industrial Research Collaboration” guides the teaching direction for communication design majors, and can help to cultivate communication design talents who are conpetent for the post provided.