AUTHOR=Chen Zhen , Yu Xiaoxuan 

TITLE=Adoption of Human Personality Development Theory Combined With Deep Neural Network in Entrepreneurship Education of College Students

JOURNAL=Frontiers in Psychology

VOLUME=Volume 11 - 2020

YEAR=2020

URL=https://www.frontiersin.org/journals/psychology/articles/10.3389/fpsyg.2020.01346

DOI=10.3389/fpsyg.2020.01346

ISSN=1664-1078

ABSTRACT=In order to study the application value of personality development theory and deep learning neural network in college students' entrepreneurship psychological education courses, the probability matrix factorization (PMF) algorithm is introduced to optimize the deep neural network algorithm model. Based on the personality development theory, a recommendation algorithm system for entrepreneurial projects under optimized deep neural network is established. Then 128 students of Northeastern University are divided into experimental group and control group. In addition to the normal courses of entrepreneurship psychology education, students in the experimental group are taught the entrepreneurship project recommendation system based on optimized deep neural network designed in this research, while students in the control group are taught entrepreneurship psychology education normally. The intervention effect before and after entrepreneurship education is evaluated by the questionnaire of college students' entrepreneurial intention and college students' entrepreneurial mental resilience scale. The results show that the system recall rate and accuracy based on the algorithm in this research have been significantly higher than that of PMF algorithm and deep belief network (DBN) algorithm, and the difference is statistically significant (P<0.05); the mean square error (MSE) of the proposed algorithm is significantly smaller than that of PMF algorithm and DBN algorithm, and the difference is statistically significant (P<0.05); the improvement of entrepreneurial toughness, entrepreneurial strength, optimism, entrepreneurial possibility, and behavioral tendency of the experimental group after test was significantly higher than that of the control group (P<0.05), which shows that compared with traditional algorithms, the performance of recommendation algorithm for entrepreneurial projects based on the theory of personality development and the optimized deep neural network is better, which can effectively improve the entrepreneurial intention and psychological resilience of college students.