Ratio control and fault handling of aero-naval traction systems using neural network theory

2021 ◽  
Author(s):  
Hamid Alshareefi ◽  
Ciprian Lupu ◽  
Laith Ismail ◽  
Lich Duc Luu
Keyword(s):  
Neural Network ◽  
Network Theory ◽  
Fault Handling ◽  
Neural Network Theory

scholarly journals Transient Power Quality Recognition Based on BP Neural Network Theory

2012 ◽  
Vol 16 ◽  
pp. 1386-1392 ◽  
Author(s):  
Xu Tongyu ◽  
Zheng wei ◽  
Sun Peng ◽  
Zhang Qin
Keyword(s):  
Neural Network ◽  
Power Quality ◽  
Bp Neural Network ◽  
Network Theory ◽  
Neural Network Theory ◽  
Transient Power Quality

Soft case-based reasoning

2005 ◽  
Vol 20 (3) ◽  
pp. 267-269 ◽  
Author(s):  
WILLIAM CHEETHAM ◽  
SIMON SHIU ◽  
ROSINA O. WEBER
Keyword(s):  
Neural Network ◽  
Fuzzy Logic ◽  
Soft Computing ◽  
Network Theory ◽  
Probabilistic Reasoning ◽  
Case Based Reasoning ◽  
Case Representation ◽  
Soft Computing Techniques ◽  
Neural Network Theory ◽  
Case Based

The aim of this commentary is to discuss the contribution of soft computing—a consortium of fuzzy logic, neural network theory, evolutionary computing, and probabilistic reasoning—to the development of case-based reasoning (CBR) systems. We will describe how soft computing has been used in case representation, retrieval, adaptation, reuse, and case-base maintenance, and then present a brief summary of six CBR applications that use soft computing techniques.

Creep Behavior Prediction Research of T92 Steel Based on BP Neural Network

2013 ◽  
Vol 467 ◽  
pp. 203-207
Author(s):  
Jian Liu
Keyword(s):  
Neural Network ◽  
Creep Behavior ◽  
Bp Neural Network ◽  
Network Theory ◽  
Experimental Results ◽  
Behavior Prediction ◽  
Forecast Precision ◽  
Network Method ◽  
Simulation Results ◽  
Neural Network Theory

Based on the BP neural network theory, the creep rate prediction model of T92 steel was established under multiple stress levels. Obtained the experimental results and using the model, the experimental results were trained. The results show that the simulation results match the measured results well with a high forecast precision. The BP neural network method can serve as research on T92 steel creep behavior.

BP Neural Network Model on Choice of Project Manager for Highway Slope Treatment

2014 ◽  
Vol 505-506 ◽  
pp. 274-277
Author(s):  
Bin Wang ◽  
Yong Tao Gao
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Neural Network Model ◽  
Bp Neural Network ◽  
Network Theory ◽  
Influence Factors ◽  
Project Manager ◽  
Slope Treatment ◽  
Neural Network Theory ◽  
Bp Neural Network Model

To get the quantified indexes of comprehensive capacity about project manager, based on the modal on artificial neural network theory, different influence factors about choice of project manager for highway slope treatment were analyzed , identified, quantified and evaluated , then comprehensive capacity of the manager were analyzed. Such procedure provided a new method for choice of project manager for highway slope treatment.

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