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基于蜂群学习的工业大数据共享方法研究 - 中国知网
Source: kns.cnki.net
Article summary:
1. This article proposes a method for industrial big data sharing based on swarm learning and Longan Chain.
2. The data is divided into user dimension and user feature dimension, and two algorithms are proposed for different types of data.
3. A scoring method is used to select the model with the highest score for integration.
Article analysis:
The article is generally trustworthy and reliable, as it provides a detailed description of the proposed method for industrial big data sharing based on swarm learning and Longan Chain. The article also provides evidence to support its claims, such as experiments conducted to verify that the proposed method can prevent privacy leakage during learning process and enhance trust between nodes participating in the federated learning process. There does not appear to be any bias or one-sided reporting in the article, as both sides of the argument are presented equally. Furthermore, there are no unsupported claims or missing points of consideration in the article, as all claims are supported by evidence from experiments conducted. Additionally, there are no promotional contents or partiality present in the article, as it focuses solely on presenting an objective overview of the proposed method without any attempts at promoting it. Finally, possible risks associated with using this method are noted in the article, such as potential privacy leakage during learning process and malicious nodes uploading low-quality models.