实时通信网络故障预测的时间分类

M. Jaudet, N. lqbal, A. Hussain, K. Sharif
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引用次数: 11

摘要

提出了一种新的电信网络fjldt预测时间分类方法。选取巴基斯坦电信(Pakistan Telecom, PTCL)的全国数据网络作为研究分类算法的基础,以预测故障是否会导致大量用户电路无法正常运行。解决的主要问题是评估警报和开发新的机器学习工具,以帮助克服互操作性问题。这项工作背后的动机是协助人类操作员并最大限度地减少警报评估的成本
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Temporal classification for fault-prediction in a real-world telecommunications network
This paper presents a new temporal classification approach for fjldt-prediction in a Telecommutnications Network. The countrvwide data network of Pakistan Telecom (PTCL) has been selected as a basis for the investigation of classification algor-ithms to predict flults beJbre they stop a large numnber of users' circuits from normal operation. The main problenms addressed are the evalluation of alarms and clevelopment of newi, machine learning tools to help overcome the interoperabilitv issues. The motivation behind this work is to assist humian operators and nminimize the cost of the alarm evalulation
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