Accurate Detecting Method for Fractional Harmonic

2011 ◽  
Vol 383-390 ◽  
pp. 4365-4370
Author(s):  
Ping Wang ◽  
Bao Hua Cheng ◽  
Zhi Bin Zhang
Keyword(s):  
Neural Network ◽  
High Precision ◽  
Dynamic Characteristics ◽  
Network Theory ◽  
Hopfield Neural Network ◽  
Integral Parameter ◽  
Simulation Results ◽  
Neural Network Theory ◽  
Detecting Method

This paper introduces a Hopfield neural network theory to deduce the model of the detection of fractional harmonic. It also discusses the setting method of integral parameter. The simulation results show that the method has high precision and the dynamic characteristics of the system are relevant to the integral parameter.

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.

The Design of a Wavelet-Based Neural Network Adaptive Filter

2013 ◽  
Vol 860-863 ◽  
pp. 2791-2795
Author(s):  
Qian Xiao ◽  
Yu Shan Jiang ◽  
Ru Zheng Cui
Keyword(s):  
Neural Network ◽  
Wavelet Transform ◽  
Real Time ◽  
Adaptive Filter ◽  
Adaptive Algorithm ◽  
Distributed Storage ◽  
Hopfield Neural Network ◽  
Lms Algorithm ◽  
The Neural Network ◽  
Simulation Results

Aiming at the large calculation workload of adaptive algorithm in adaptive filter based on wavelet transform, affecting the filtering speed, a wavelet-based neural network adaptive filter is constructed in this paper. Since the neural network has the ability of distributed storage and fast self-evolution, use Hopfield neural network to implement adaptive filter LMS algorithm in this filter so as to improve the speed of operation. The simulation results prove that, the new filter can achieve rapid real-time denoising.

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.

Sign in / Sign up

Export Citation Format

Share Document