scholarly journals Psychological Assessment Data Processing Model Based on Neural Network Theory

2016 ◽  
Author(s):  
Xiaowang Chen
Keyword(s):  
Neural Network ◽  
Data Processing ◽  
Psychological Assessment ◽  
Network Theory ◽  
Assessment Data ◽  
Model Based ◽  
Neural Network Theory

Simulation of Failure Detection Based on Neural Network for No-Ball Mill

2011 ◽  
Vol 201-203 ◽  
pp. 627-631
Author(s):  
Kun Shan Li ◽  
Xin Hua Wang ◽  
Wen Ming Wang
Keyword(s):  
Neural Network ◽  
Data Processing ◽  
Network Theory ◽  
Ball Mill ◽  
Detection System ◽  
Structural Characteristics ◽  
Failure Detection ◽  
The Neural Network ◽  
Point Set ◽  
Neural Network Theory

According to the structural characteristics of non-ball mill, using the neural network theory to select and measure point, set the failure mode, analyze and determine the cause of malfunction. The newly developed fault detection system was used to simulative detect fault. Through data processing, the results can be directly derived which could be fed back into the design of non-ball mill, thereby improving the design.

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.

Model-based optimal attitude and positioning control of small-scale unmanned helicopter

Robotica ◽  
2005 ◽  
Vol 23 (1) ◽  
pp. 51-63 ◽  
Author(s):  
Jinok Shin ◽  
Kenzo Nonami ◽  
Daigo Fujiwara ◽  
Kensaku Hazawa
Keyword(s):  
Network Theory ◽  
Attitude Control ◽  
Position Control ◽  
Small Scale ◽  
Unmanned Helicopter ◽  
Positioning Control ◽  
Model Based ◽  
Loop Dynamics ◽  
Neural Network Theory ◽  
Dynamics Simulations

In this paper, we propose a model-based control system design for autonomous flight and guidance control of a small-scale unmanned helicopter. Small-scale unmanned helicopters have been studied by way of fuzzy and neural network theory, but control that is not based on a model fails to yield good stabilization performance. For this reason, we design a mathematical model and a model-based controller for a small-scale unmanned helicopter system. In order to realize a fully autonomous small-scale unmanned helicopter, we have designed a MIMO attitude controller and a trajectory controller equipped with a Kalman filter-based LQI for a small-scale unmanned helicopter. The design of the trajectory controller takes into consideration the characteristics of attitude closed-loop dynamics. Simulations and experiments have shown that the proposed scheme for attitude control and position control is very useful.

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