Abstract
With the informationization of the development of party members in colleges and universities, the traditional management platform has been unable to meet the recommendation work of party members in colleges and universities. By analyzing the shortcomings of the existing party member management platform, this paper proposes a student party member development recommendation model based on the grid platform deep learning mode. Under the grid platform, the artificial intelligence method of deep learning training is used to set the development object. Different parameters and parameter weights are set, and repeated training makes the constructed model more optimized, thus obtaining the recommended queue, solving the manual operation mode of daily work, reducing the working time, improving the work efficiency, and making the whole process more intelligent.
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Acknowledgements
This work was supported by the project of Nature Scientific Foundation of Heilongjiang Province (F2016038).
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Guo, Ww., Liu, F. (2020). Research and Design of Student Party Member Development Recommendation Model Based on Grid Platform Deep Learning Mode. In: Yang, CT., Pei, Y., Chang, JW. (eds) Innovative Computing. Lecture Notes in Electrical Engineering, vol 675. Springer, Singapore. https://doi.org/10.1007/978-981-15-5959-4_213
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DOI: https://doi.org/10.1007/978-981-15-5959-4_213
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