Evaluation of Innovation and Entrepreneurship Education for College Students Based on BP Neural Network

Abstract

With the steady advancement, innovation, and entrepreneurship education (IEE) in higher education institutions has gradually become a powerful measure and a vital approach for cultivating talents. Therefore, establishing a complete and feasible evaluation system for IEE is vital for the enhancement of education level and quality. On the basis of the principles for the evaluating system, the study selected the evaluation indicators for IEE. Then, the adaptive flower pollination algorithm was used to evolve the BP’s initial weight and threshold applied to the evaluation of the IEE of college students. The improved BP network had a faster speed in the first to fifth iteration, and the mean square error converged between 10-7 and 10-6. In the comparison of fitness values, the method converged only in the 16th generation, and the fitness value was stable at about 1.95. In practical application, the error rate of this method was about 13%, and it had a high accuracy rate. Its high accuracy indicated that this method could effectively evaluate the IEE in higher education institutions, and provided certain technical support for the cultivation of innovative talents.