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基于 MOPSO-CD-DNN 模型的发达国家中小学文化与传统教育比较研究。

A Comparative Study of Cultural and Traditional Education in Primary and Secondary Schools in Developed Countries Based on the MOPSO-CD-DNN Model.

机构信息

Hubei Business College, Wuhan 430070, Hubei, China.

出版信息

Comput Intell Neurosci. 2022 Jul 12;2022:3973763. doi: 10.1155/2022/3973763. eCollection 2022.

Abstract

In today's globalization, cultural and traditional education in primary and secondary schools has become the core of a country's future development, and how to improve the educational effect of cultural and traditional education in primary and secondary schools and find the development direction of cultural and traditional education has become the top priority. In response to this problem, this study proposes a MOPSO-CD-DNN hybrid prediction model, which introduces an optimization algorithm to optimize the parameters of the deep learning model. In this study, multiple benchmark models and evaluation methods are used for comparative research. The results show that the MOPSO-CD-DNN model has significant advantages in both prediction accuracy and prediction stability. Compared with other models, the prediction accuracy value (average) is improved by 4.66%, 7.43%, and 9.25%, and the standard deviation ( value) is decreased by 0.001, 0.0502, and 0.0413, indicating its effectiveness and applicability to cultural tradition education. In addition, the introduction of the multiobjective optimization algorithm significantly improves the generalization ability of the model, and the prediction effect is significantly better than the single-objective optimization algorithm.

摘要

在当今全球化的背景下,中小学的文化和传统教育已成为国家未来发展的核心,如何提高中小学文化和传统教育的教育效果,寻找文化和传统教育的发展方向,已成为当务之急。针对这一问题,本研究提出了一种 MOPSO-CD-DNN 混合预测模型,该模型引入了一种优化算法来优化深度学习模型的参数。本研究采用了多个基准模型和评估方法进行对比研究。结果表明,MOPSO-CD-DNN 模型在预测精度和预测稳定性方面均具有显著优势。与其他模型相比,该模型的预测精度值(平均值)提高了 4.66%、7.43%和 9.25%,标准差(值)降低了 0.001、0.0502 和 0.0413,表明其在文化传统教育中的有效性和适用性。此外,多目标优化算法的引入显著提高了模型的泛化能力,预测效果明显优于单目标优化算法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2325/9296323/dc4f0a04a2aa/CIN2022-3973763.001.jpg

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