针对用户数据空间分布不平衡的无线网络的基于集合和成本敏感学习的根本原因诊断方案

IF 7.3 2区计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS

Science China Information Sciences Pub Date : 2024-06-25 DOI:10.1007/s11432-023-4055-1

Qi Wang, Zhiwen Pan, Nan Liu

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引用次数: 0

摘要

提出了一种可容忍不平衡用户数据的新型特征提取方法。对成本敏感的 SVM 为不同严重程度的故障分配不同的误分类成本，以优化故障诊断过程。仿真结果证明了所提算法的有效性和优越性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

An ensemble and cost-sensitive learning-based root cause diagnosis scheme for wireless networks with spatially imbalanced user data distribution

A novel feature extraction method that can tolerate imbalanced user data is proposed. A cost-sensitive SVM assigns different misclassification costs to faults with different severity levels to optimize the cause diagnosis process. The simulation results demonstrate the effectiveness and superiority of the proposed algorithm.

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来源期刊

Science China Information Sciences COMPUTER SCIENCE, INFORMATION SYSTEMS-

CiteScore

12.60

自引率

5.70%

发文量

224

审稿时长

8.3 months

期刊介绍： Science China Information Sciences is a dedicated journal that showcases high-quality, original research across various domains of information sciences. It encompasses Computer Science & Technologies, Control Science & Engineering, Information & Communication Engineering, Microelectronics & Solid-State Electronics, and Quantum Information, providing a platform for the dissemination of significant contributions in these fields.