CBO-Based TDR Approach for Wiring Network Diagnosis

2017 ◽  
pp. 329-348
Author(s):  
Hamza Boudjefdjouf ◽  
Francesco de Paulis ◽  
Houssem Bouchekara ◽  
Antonio Orlandi ◽  
Mostafa K. Smail
Keyword(s):  
Network Diagnosis

Mo1935 Using Contrast-Enhanced Ultrasonography (CEUS) Time-Intensity Curves (TICs) as Classifiers in Neural Network Diagnosis of Focal Liver Lesions

2012 ◽  
Vol 142 (5) ◽  
pp. S-1004 ◽  
Author(s):  
Costin T. Streba ◽  
Dan Ionut Gheonea ◽  
Larisa D. Sandulescu ◽  
Liliana Streba ◽  
Tudorel Ciurea ◽  
...  
Keyword(s):  
Neural Network ◽  
Focal Liver Lesions ◽  
Liver Lesions ◽  
Contrast Enhanced ◽  
Contrast Enhanced Ultrasonography ◽  
Network Diagnosis

scholarly journals MAMNID: A Load Balance Network Diagnosis Model Based on Mobile Agents

2012 ◽  
Vol 03 (04) ◽  
pp. 281-294 ◽  
Author(s):  
Thomas Djotio Ndié ◽  
Claude Tangha ◽  
Guy Bertrand Fopak
Keyword(s):  
Load Balance ◽  
Mobile Agents ◽  
Model Based ◽  
Diagnosis Model ◽  
Network Diagnosis

Fault Diagnosis of Transformer Based on RBF Neural Network

2014 ◽  
Vol 571-572 ◽  
pp. 201-204
Author(s):  
Jian Li Yu ◽  
Zhe Zhang
Keyword(s):  
Neural Network ◽  
Fault Diagnosis ◽  
Rbf Neural Network ◽  
High Energy ◽  
Ratio Method ◽  
Matlab Simulation ◽  
Medium Temperature ◽  
The Neural Network ◽  
Transformer Fault ◽  
Network Diagnosis

According to the characteristics of fault types of the transformer ,RBF neural network is used to diagnose transformer fault. The paper regards six gases as inputs of the neural network and establishes RBF neural network model which can diagnose six transformer faults: low temperature overheat, medium temperature overheat, high temperature overheat, low energy discharge, high energy discharge and partial discharge . The Matlab simulation studies show that transformer fault diagnosis model based on RBF neural network diagnosis for failure beyond the traditional three-ratio method. The rate of the transformer fault diagnosis accuracy reaches 91.67% which is also much higher than the traditional three ratio method.

Neural network diagnosis of heart disease

2015 ◽  
Author(s):  
Ebenezer O. Olaniyi ◽  
Oyebade K. Oyedotun ◽  
Abdulkader Helwan ◽  
Khashman Adnan
Keyword(s):  
Neural Network ◽  
Heart Disease ◽  
Network Diagnosis

A Lightweight Approach to Distributed Network Diagnosis under Uncertainty

2009 ◽  
Author(s):  
Francisco Javier García-Algarra ◽  
Pablo Arozarena-Llopis ◽  
Sergio García-Gómez ◽  
Álvaro Carrera-Barroso
Keyword(s):  
Distributed Network ◽  
Network Diagnosis

Autonomous network diagnosis from the carrier perspective [Invited]: publisher’s note

2019 ◽  
Vol 12 (3) ◽  
pp. 1
Author(s):  
Takafumi Tanaka ◽  
Akira Hirano ◽  
Shoukei Kobayashi ◽  
Takuya Oda ◽  
Seiki Kuwabara ◽  
...  
Keyword(s):  
Autonomous Network ◽  
Network Diagnosis

Demonstration of a Novel Framework for Proactive Maintenance Using Failure Prediction and Bit Lossless Protection With Autonomous Network Diagnosis System

2020 ◽  
Vol 38 (9) ◽  
pp. 2695-2702 ◽  
Author(s):  
Fumikazu Inuzuka ◽  
Takuya Oda ◽  
Takafumi Tanaka ◽  
Kei Kitamura ◽  
Seiki Kuwabara ◽  
...  
Keyword(s):  
Failure Prediction ◽  
Diagnosis System ◽  
Autonomous Network ◽  
Network Diagnosis ◽  
Proactive Maintenance
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