基于BP神经网络的大学生创新创业教育评价

Pub Date : 2023-09-29 DOI:10.46300/9109.2023.17.8
Song Wang
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引用次数: 0

摘要

随着我国经济的不断发展,创新创业教育逐渐成为高校培养人才的有力措施和重要途径。因此,建立一套完整、可行的教育评价体系,对提高教育水平和质量至关重要。在评价体系原则的基础上,选择了评价指标。然后,利用自适应授粉算法对BP的初始权值和阈值进行演化,应用于大学生IEE的评价。改进后的BP网络在第1 ~ 5次迭代中速度更快,均方误差收敛在10-7 ~ 10-6之间。在适应度值的比较中,该方法仅在第16代收敛,适应度值稳定在1.95左右。在实际应用中,该方法的错误率约为13%,具有较高的准确率。结果表明,该方法具有较高的准确性,能够有效地评价高校创新人才,为创新人才的培养提供一定的技术支持。
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Evaluation of Innovation and Entrepreneurship Education for College Students Based on BP Neural Network
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.
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