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    Management and entrepreneurship management mechanism of college students based on support vector machine algorithm

    Autor: 
    Wang, C.
    ;
    Dong, Y
    ;
    Xia, Y.
    ;
    Li, G.
    ;
    Martínez, O.S
    ;
    González-Crespo, Rubén (1)
    Fecha: 
    2020
    Palabra clave: 
    college students; employment and entrepreneurship; management mechanism; support vector machine algorithm; Scopus; WOS(2)
    Tipo de Ítem: 
    article
    URI: 
    https://reunir.unir.net/handle/123456789/12463
    DOI: 
    https://doi.org/10.1111/coin.12430
    Dirección web: 
    https://onlinelibrary.wiley.com/doi/10.1111/coin.12430
    Resumen:
    For the employment and entrepreneurship management of college students, the application of big data technology can effectively improve their work efficiency, that is, the support vector machine algorithm is applied to the employment and entrepreneurship management of college students. Based on deep learning technology, the deep neural network is constructed based on SVR and restrictive Boltzmann machine, namely, SVR-DBN, including theoretical derivation of model architecture, design and selection of model training algorithms, and the modeling steps and flow charts are given, and finally applied to the influence factor analysis. The multiangle comparison proves that the proposed depth model has excellent feature extraction ability and regression prediction. The results show that the algorithm has higher accuracy and has a 26% improvement over traditional algorithms. The research is of great significance to the improvement of the efficiency of employment and entrepreneurship management and the application of support vector machine algorithms. © 2020 Wiley Periodicals LLC.
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