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International Journal of Networking and Virtual Organisations最新文献

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Discussion on the Current Situation and Quality Evaluation Model of Online Course Teaching in Universities Based on Social Network Analysis 基于社会网络分析的高校网络课程教学现状及质量评价模型探讨
Q4 Decision Sciences Pub Date : 2023-01-01 DOI: 10.1504/ijnvo.2023.10059366
WuYi Zhou N.A.
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引用次数: 0
Using digital health to support superior preparedness to enable better preparedness and readiness to combat pandemics: a scoping review 利用数字卫生支持卓越防范,以更好地防范和准备抗击大流行病:范围审查
Q4 Decision Sciences Pub Date : 2023-01-01 DOI: 10.1504/ijnvo.2023.10059780
Nilmini Wickramasinghe, Rima Gibbings
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引用次数: 0
An Efficient Optimal Load Balancing Algorithm For Distributed File Systems in Cloud Environment 云环境下分布式文件系统的一种高效最优负载均衡算法
Q4 Decision Sciences Pub Date : 2023-01-01 DOI: 10.1504/ijnvo.2023.10056519
Manjula H. Nebagiri, Latha P. H
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引用次数: 0
Application of Improved Clustering Algorithm in Precision Poverty Auditing - An Example from Region D 改进聚类算法在精准贫困审计中的应用——以D地区为例
Q4 Decision Sciences Pub Date : 2023-01-01 DOI: 10.1504/ijnvo.2023.10057568
Yantai Zhang
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引用次数: 0
Privacy information encryption for cross-border e-commerce users based on social network analysis 基于社交网络分析的跨境电商用户隐私信息加密
Q4 Decision Sciences Pub Date : 2023-01-01 DOI: 10.1504/ijnvo.2023.10059480
Ji Zhang, Feng Gao, Na Wang
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引用次数: 0
Application of improved clustering algorithm in precision poverty auditing - an example from region D 改进聚类算法在精准贫困审计中的应用——以D地区为例
Q4 Decision Sciences Pub Date : 2023-01-01 DOI: 10.1504/ijnvo.2023.133871
Yantai Zhang
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引用次数: 0
Application analysis of data mining based on improved decision tree in English flipped classroom teaching 基于改进决策树的数据挖掘在英语翻转课堂教学中的应用分析
Q4 Decision Sciences Pub Date : 2023-01-01 DOI: 10.1504/ijnvo.2023.133848
Xianghong Yin
This study aims to analyse the application of data mining based on improve decision in English flipped classroom teaching. The experimental results show that the improved C4.5 algorithm had a better performance than ID3 algorithm and C4.5 algorithm and CART algorithm. In terms of accuracy rate, the four algorithms can be ranked as improved C4.5 algorithm, C4.5 algorithm, ID3 algorithm, and CART algorithm from high to low. Moreover, the improved C4.5 algorithm had the lowest error rate among the four algorithms. Under the same number of training samples, the improved C4.5 algorithm takes the least time at the least memory cost. Therefore, the improved C4.5 algorithm is adopted to construct a data mining model for English flipped classroom teaching and promote the research on English flipped classroom teaching.
本研究旨在分析基于改进决策的数据挖掘在英语翻转课堂教学中的应用。实验结果表明,改进的C4.5算法比ID3算法、C4.5算法和CART算法具有更好的性能。四种算法的准确率由高到低依次为改进的C4.5算法、C4.5算法、ID3算法、CART算法。改进的C4.5算法在四种算法中错误率最低。在相同的训练样本数量下,改进的C4.5算法以最小的内存开销花费最少的时间。因此,采用改进的C4.5算法构建英语翻转课堂教学的数据挖掘模型,推动英语翻转课堂教学的研究。
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引用次数: 0
An application of neural network algorithm model based on improved multi-expression programming in English language education practice 基于改进多表达式编程的神经网络算法模型在英语教学实践中的应用
Q4 Decision Sciences Pub Date : 2023-01-01 DOI: 10.1504/ijnvo.2023.133860
Yue Feng
In the field of English education, neural network algorithm can effectively predict and evaluate teaching, and significantly improve the quality of education and teaching. Therefore, a neural network English teaching evaluation prediction model based on multi expression programming is proposed. Through the research on neural network and genetic algorithm (GA), it is found that flexible neural tree cannot optimise parameters and results at the same time. Therefore, a neural network algorithm model (MEP) based on multi expression programming is proposed to solve the problem, and the MEP-NN English teaching evaluation model is constructed by optimising the model parameters with evolutionary algorithm. The model is applied to the English teaching process to achieve the evaluation of English teaching quality. The results show that in the mean square error performance test of multiple algorithms, achieving convergence after 500 iterations, with an MSE value of 0.02 and the best error performance; in the English class comprehensive quality prediction, the proposed MEP-NN algorithm has the best prediction accuracy, with a prediction mean of 86.56 points, closest to the actual value of 86 score, with a prediction accuracy of 94.56%. This shows that the proposed MEP-NN algorithm has excellent performance.
在英语教育领域,神经网络算法可以有效地预测和评估教学,显著提高教育教学质量。为此,提出了一种基于多表达式编程的神经网络英语教学评价预测模型。通过对神经网络和遗传算法的研究,发现柔性神经树不能同时对参数和结果进行优化。为此,提出了一种基于多表达式规划的神经网络算法模型(MEP)来解决该问题,并利用进化算法对模型参数进行优化,构建了MEP- nn英语教学评价模型。将该模型应用到英语教学过程中,实现对英语教学质量的评价。结果表明,在多种算法的均方误差性能测试中,经过500次迭代后实现收敛,MSE值为0.02,误差性能最佳;在英语课堂综合质量预测中,本文提出的MEP-NN算法预测精度最好,预测均值为86.56分,最接近86分的实际值,预测精度为94.56%。这表明所提出的MEP-NN算法具有优异的性能。
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引用次数: 0
Research on government network public opinion monitoring algorithm under the background of sustainable smart government 可持续智慧政府背景下的政府网络舆情监测算法研究
Q4 Decision Sciences Pub Date : 2023-01-01 DOI: 10.1504/ijnvo.2023.133844
Shiwei Zhang
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引用次数: 0
E-commerce Collaborative Filtering Recommendation Method Based on Social Network User Relationship 基于社交网络用户关系的电子商务协同过滤推荐方法
Q4 Decision Sciences Pub Date : 2023-01-01 DOI: 10.1504/ijnvo.2023.10059365
Pei Li, Miao Jiang
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引用次数: 0
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International Journal of Networking and Virtual Organisations
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