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International Journal of Web Engineering and Technology最新文献

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Personalised learning systems: drivers of employees' behavioural intention 个性化学习系统:员工行为意向的驱动因素
Q4 Computer Science Pub Date : 2023-01-01 DOI: 10.1504/ijwet.2023.133621
Sandra Schlagheck, Gerhard Schewe
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引用次数: 0
Application of chorus teaching model for pedagogical quality assessment on software engineering skills teaching 合唱教学模式在软件工程技能教学质量评价中的应用
Q4 Computer Science Pub Date : 2023-01-01 DOI: 10.1504/ijwet.2023.133624
Qidong Kang
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引用次数: 0
Building a sustainable public management system based on the environmental Kuznets curve 构建基于环境库兹涅茨曲线的可持续公共管理体系
Q4 Computer Science Pub Date : 2023-01-01 DOI: 10.1504/ijwet.2023.132869
Yundong Liu
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引用次数: 0
A study on the economic and sustainable development forecast of rural tourism industry based on ANN 基于神经网络的乡村旅游产业经济与可持续发展预测研究
Q4 Computer Science Pub Date : 2023-01-01 DOI: 10.1504/ijwet.2023.133610
Li Huang, Jingwei Zhai
This study establishes a rural tourism industry economic sustainability prediction model based on the back propagation neural network (BP) in artificial neural network (ANN). It selects the indicators that have a large influence on the rural tourism industry economic sustainability prediction, and takes the four indicators with the highest weight percentage as the input of the prediction model, and verify the validity of the model. The result shows that the average relative prediction error of the univariate BP neural network was smaller than the grey model (GM). The average absolute value of relative prediction error for the multivariate BP neural network was smaller than the prediction error value of the univariate BP neural network model. The AUC value of the multivariate BP prediction model based on this study is 0.93. This research model improves the accuracy of predicting the sustainable economic development of the rural tourism industry.
本研究基于人工神经网络(ANN)中的反向传播神经网络(BP)建立了乡村旅游产业经济可持续性预测模型。选取对乡村旅游产业经济可持续性预测影响较大的指标,将权重百分比最高的4个指标作为预测模型的输入,验证模型的有效性。结果表明,单变量BP神经网络的平均相对预测误差小于灰色模型(GM)。多元BP神经网络相对预测误差的平均绝对值小于单变量BP神经网络模型的预测误差值。基于本研究的多变量BP预测模型AUC值为0.93。该研究模型提高了对乡村旅游产业经济可持续发展预测的准确性。
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引用次数: 0
A stepwise audit framework for keyword selection and estimating visibility for low performing websites: a study of cmsdu.org 一个逐步审计框架的关键字选择和估计能见度低表现的网站:cmsdu.org的研究
Q4 Computer Science Pub Date : 2023-01-01 DOI: 10.1504/ijwet.2023.132870
Prakrit Saikia, Himadri Barman
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引用次数: 0
Communication media as mediators of telework frequency and knowledge sharing in Japan under COVID-19 新冠肺炎疫情下日本远程办公频率与知识共享的媒介作用
Q4 Computer Science Pub Date : 2023-01-01 DOI: 10.1504/IJWET.2023.131139
Rémy Magnier-Watanabe
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引用次数: 0
A study on the economic and sustainable development forecast of rural tourism industry based on ANN 基于神经网络的乡村旅游产业经济与可持续发展预测研究
Q4 Computer Science Pub Date : 2023-01-01 DOI: 10.1504/ijwet.2023.10059296
Li Huang, Jingwei Zhai
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引用次数: 0
Research on the application of association rules based on information entropy in human resource management 基于信息熵的关联规则在人力资源管理中的应用研究
Q4 Computer Science Pub Date : 2023-01-01 DOI: 10.1504/ijwet.2023.10059299
Lei Li, Yi Wang
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引用次数: 0
Research on the privacy protection model of government cyber security in smart cities based on big data 基于大数据的智慧城市政府网络安全隐私保护模式研究
Q4 Computer Science Pub Date : 2023-01-01 DOI: 10.1504/ijwet.2023.133615
Gongping Chen, Hong Wang
With the escalation of hacking methods, the existing network security privacy model can no longer fully guarantee the security of private information. To solve the problem of poor security performance of the traditional privacy protection model, the research proposes an improved privacy protection algorithm based on the SMART algorithm by optimising the hierarchical processing of the original sensing data, which encrypts and protects the private data, and embeds the privacy protection algorithm into the government network security privacy protection model. The experimental results show that proposed algorithm has a privacy exposure probability of 0.05, a fusion accuracy of 89% and a network energy consumption of 82.5%, which is all better than comparison algorithms. It can provide better security protection to the government cybersecurity privacy protection model, and also provide a new idea for the privacy protection method of the privacy protection model.
随着黑客手段的不断升级,现有的网络安全隐私模型已经不能完全保证个人信息的安全。针对传统隐私保护模型安全性能差的问题,本研究提出了一种基于SMART算法的改进隐私保护算法,通过对原始感知数据的分层处理进行优化,对隐私数据进行加密保护,并将隐私保护算法嵌入到政府网络安全隐私保护模型中。实验结果表明,该算法的隐私暴露概率为0.05,融合准确率为89%,网络能耗为82.5%,均优于比较算法。它可以为政府网络安全隐私保护模式提供更好的安全保护,也为隐私保护模式的隐私保护方法提供了新的思路。
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引用次数: 0
Predicting the enterprise tax risk using improved multilayer perceptive vector machine 利用改进的多层感知向量机预测企业税收风险
Q4 Computer Science Pub Date : 2023-01-01 DOI: 10.1504/ijwet.2023.10059297
Yi Liu
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引用次数: 0
期刊
International Journal of Web Engineering and Technology
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