RA-QoS:一个基于自动编码器的强大的QoS预测器,用于高度准确的Web服务QoS预测
Shun Fu1, Junnan Li1, Lufeng Wang1
1Chongqing Industry Polytechnic College, Chongqing, China.
PeerJ. Computer science
|June 26, 2025
概括
我们开发了一个基于自动编码器的强大的服务质量 (QoS) 预测器 (RA-QoS),可以有效地处理杂的数据和异常值. 这种新的方法可以提高在线服务推的预测准确性.
科学领域:
- 计算机科学 计算机科学
- 人工智能的人工智能
- 机器学习 机器学习
背景情况:
- 准确的服务质量 (QoS) 预测对于面向服务的应用程序至关重要.
- 深度神经网络 (DNN) 的 QoS 预测器由于 L2 规范的敏感性而与杂的数据和异常值作斗争.
- 现有的方法在现实世界QoS预测场景中缺乏稳定性.
研究的目的:
- 提出一种基于自编码器的强大的 QoS 预测器 (RA-QoS).
- 提高 QoS 预测模型的稳定性和准确性.
- 解决当前基于DNN的预测器在处理杂的QoS数据方面的局限性.
主要方法:
- 使用混合损失函数 (偏差,训练偏差,L1-规范,L2-规范) 开发了一个强大的自动编码器.
- 将预处理和训练偏差纳入RA-QoS模型.
- 在两个现实世界QoS数据集上进行了广泛的实验.
主要成果:
- 与最先进的模型相比,RA-QoS预测器显示出与异常值的优越稳定性.
- 在现实数据集上的 QoS 预测中实现了更高的准确性.
- 混合损失功能有效地减少了噪音和偏差的影响.
结论:
- 拟议的RA-QoS模型为QoS预测提供了更强大,更准确的解决方案.
- 在Web服务环境中,RA-QoS有效处理杂数据和异常值.
- 这种方法可以提高在线应用程序中服务建议的可靠性.
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