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In order to improve the adaptive scheduling ability of the innovation and entrepreneurship education model for college students, a brain computing-based innovation and entrepreneurship education model for college students is proposed. Through career-planning education, team training will gradually cultivate the leadership skills of entrepreneurs and improve the overall level of innovation and entrepreneurship of college students. The paper proposes to use the fuzzy neural network algorithm to analyze the control constraint parameters of the college students’ innovation and entrepreneurship education model and optimize the design of the control objective function of the university. The control of students’ innovation and entrepreneurship education model is carried out using quantitative optimization methods. The fuzzy neural network is used to identify the control rights of college students’ innovation and entrepreneurship education model through label recognition technology, and the control objective model of college students’ innovation and entrepreneurship education model is constructed. The adaptive load-balancing control method is adopted to control the innovation and entrepreneurship education model of college students. Research shows that this method has a good balance and adaptive control ability in the construction of college students’ innovation and entrepreneurship education model.

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An Exploratory Research on Constructing a Model of Innovation and Entrepreneurship Education for College Students Based on Fuzzy Neural Network Algorithm