基于pso的RBF神经网络教学质量评价模型

Chang-jun Zhu, Bin Wang
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引用次数: 1

摘要

针对以往教学质量评价体系存在的问题,根据我校教学特点,运用粒子群理论和神经网络技术,建立了基于粒子群算法的教学质量评价模型。并详细说明了模型的应用过程。通过对大量实例的分析,实验结果表明,该数学模型具有较好的评价效果,能够克服传统评价模型的复杂性。与其他方法相比,该方法科学、简单、可操作性强。其结构和方法具有广阔的应用前景。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
PSO-Based RBF Neural Network Model for Teaching Quality Evaluation
In view of the problems existing in previous system of teaching quality, According to our teaching characteristics a new model of PSO-based teaching quality evaluation is set up by means of PSO theory and neural network. And the application procedure of the model is illuminated in detail. By analyzing a lot of practical examples, the experiment result indicates that this mathematical model has better appraisal effect and can overcome the complexity of traditional evaluation model. Compared with other methods, this method is scientific, simple and operable. And its structure and method will have a bright future.
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