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Machine Learning Based Automatic Diagnosis in Mobile Communication Networks
Kuo Ming Chen
*
, Tsung Hui Chang
, Kai Cheng Wang
,
Ta-Sung Lee
*
此作品的通信作者
開源智能聯網研究中心
電信工程研究所
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引文 斯高帕斯（Scopus）
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Keyphrases
Mobile Communication Network
100%
Machine Learning Based
100%
Fault Condition
100%
Automatic Diagnosis
100%
Neural Network
66%
Support Vector Machine
66%
Softmax
66%
Network Condition
66%
Diagnosis Performance
66%
Key Performance Indicators
33%
Feature Extracting
33%
Training Data
33%
Self-healing Mechanism
33%
Complex Scenarios
33%
Single Fault
33%
Multiple Faults
33%
Diagnose Faults
33%
Severity Level
33%
Self-organizing Networks
33%
Performance Management
33%
Compound Fault Diagnosis
33%
Diagnostic Algorithm
33%
Multi-fault
33%
Condition Index
33%
Fault Scenarios
33%
Condition Diagnosis
33%
Computer Science
Neural Network
100%
Support Vector Machine
100%
Communication Network
100%
Fault Diagnosis
100%
Network Condition
100%
Machine Learning
100%
Learning System
100%
Training Data
50%
Extracted Feature
50%
Key Performance Indicator
50%
Organizing Network
50%
Performance Management
50%
Diagnosis Algorithm
50%
Engineering
Communication Network
100%
Mobile Communication
100%
Fault Condition
100%
Learning System
100%
Network Condition
66%
Support Vector Machine
66%
Simulation Result
33%
Key Performance Indicator
33%
Extracted Feature
33%
Fault Diagnosis
33%
Self-Organizing Network
33%
Healing Function
33%
Chemical Engineering
Learning System
100%
Neural Network
100%
Support Vector Machine
100%