School of Finance, Jiangxi Normal University, Nanchang, Jiangxi 360100, China.
Management Science and Engineering Research Center, Jiangxi Normal University, Nanchang, Jiangxi 360100, China.
Comput Intell Neurosci. 2022 Jun 20;2022:5792694. doi: 10.1155/2022/5792694. eCollection 2022.
The development and spread of Internet technology have made it easier to find web servers. People can browse various websites to shop or pay for living expenses, which brings great convenience to life, but as a result, Internet security problems continue to appear. This article is based on a detailed theoretical analysis of mainstream algorithms, making an analysis of web logs which is of great significance and practical value. In addition, through reasoning analysis, technical support is provided for improving the weight factor of the KNN (-nearest neighbor) algorithm, and the literature research method of the SVM-KNN hybrid algorithm and the KNN classifier is proposed. This paper conducts a detailed theoretical analysis based on the mainstream algorithms that are widely used in the current classification technology and integrates the mainstream classification algorithms in real-life applications and popularization, selecting the support vector machine and KNN calculation method. In the digital economy development model, although China has a large number of netizens, obvious late-comer advantages and institutional advantages as a guarantee, due to the constraints of two key factors, capital and technology, a series of social problems have also arisen. During the transformation of the digital economy, prominent digital security issues, high-risk vulnerabilities, and increasing number of cyber-attacks, along with uneven data quality levels and lagging laws and regulations, have brought many challenges and obstacles.
互联网技术的发展和普及使得寻找网络服务器变得更加容易。人们可以浏览各种网站进行购物或支付生活费用，这给生活带来了极大的便利，但与此同时，互联网安全问题也不断出现。本文基于对主流算法的详细理论分析，对网络日志进行了分析，具有重要的意义和实用价值。此外，通过推理分析，为改进 KNN（-最近邻）算法的权重因素提供了技术支持，并提出了 SVM-KNN 混合算法和 KNN 分类器的文献研究方法。本文基于当前分类技术中广泛使用的主流算法进行了详细的理论分析，并将主流分类算法整合到实际应用和推广中，选择支持向量机和 KNN 计算方法。在数字经济发展模式下，虽然中国拥有大量网民，具有明显的后发优势和制度优势作为保障，但由于资本和技术这两个关键因素的制约，也产生了一系列社会问题。在数字经济转型过程中，突出的数字安全问题、高风险漏洞以及日益增多的网络攻击，加上数据质量水平参差不齐和法律法规滞后，带来了诸多挑战和障碍。
