An artificial neural network system for predicting the deformation of steel plate in triangle induction heating process

2013 ◽  
Vol 14 (4) ◽  
pp. 551-557 ◽  
Author(s):  
Truong-Thinh Nguyen ◽  
Young-Soo Yang ◽  
Jae-Woong Kim
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Induction Heating ◽  
Steel Plate ◽  
Heating Process ◽  
Network System ◽  
Neural Network System ◽  
Artificial Neural

Forming Complicated Surface in Shipyard Using Neural Network System

2012 ◽  
Vol 566 ◽  
pp. 470-475
Author(s):  
Truong Thinh Nguyen
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Induction Heating ◽  
Heating Process ◽  
Ann Model ◽  
Network Systems ◽  
Neural Network System ◽  
Vertical Displacements ◽  
Artificial Neural ◽  
Artificial Neural Network Ann

Determining the positions of triangle heating in and parameters of heating process are important for deforming the concave surfaces in shipyard, as well as airplane. The objective of this study was to develop an artificial neural network (ANN) model to predict positions of induction heating and parameters of heating process based on analytical solutions. This model of ANN can help manufacturers determine the positions of induction heating lines and their heating parameters to form a desired shape of plate. The backpropagation neural network systems for determining line-heating positions from object shape of plate are presented in this paper. An artificial neural network model is developed with the relationship between the desired shape of plate and the paths of induction heating. The input data are vertical displacements of plate and the output data are selected heating lines composed by the areas. The outputs of the models were positions of induction heating on plate as well as their parameters. Simulated values obtained with neural network correspond closely to the experimental results.

Early diagnosis of melanoma using an artificial neural network system

1997 ◽  
Vol 7 (Supplement 1) ◽  
pp. S58 ◽  
Author(s):  
M Burroni ◽  
G Dell??Eva ◽  
P Puddu ◽  
F Atzori ◽  
R Bono ◽  
...  
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Early Diagnosis ◽  
Network System ◽  
Neural Network System ◽  
Artificial Neural

scholarly journals Enhanced diagnostic accuracy for quantitative bone scan using an artificial neural network system: a Japanese multi-center database project

2013 ◽  
Vol 3 (1) ◽  
pp. 83 ◽  
Author(s):  
Kenichi Nakajima ◽  
Yasuo Nakajima ◽  
Hiroyuki Horikoshi ◽  
Munehisa Ueno ◽  
Hiroshi Wakabayashi ◽  
...  
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Diagnostic Accuracy ◽  
Bone Scan ◽  
Network System ◽  
System A ◽  
Neural Network System ◽  
Artificial Neural

Application of Artificial Neural Network for Cotton Boil Spoiling Disease Prediction

2010 ◽  
Vol 143-144 ◽  
pp. 233-237
Author(s):  
Fu Gui Chen ◽  
Bao Jian Zhang ◽  
Jun Hui Fu
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Expert System ◽  
Disease Prediction ◽  
Network System ◽  
Neural Network System ◽  
Average Quantity ◽  
Artificial Neural ◽  
High Output

Based on the database of cotton boil spoiling disease in Xinxiang, a computerized intelligent expert system was established by using the Reverse Model of artificial neural network. With its speediness, robustness and 100%predicting accuracy, the system can be used as an effective method to predict the trend of cotton diseases. In recent years, we have seem some reports for which use artificial neural network system to forecast the disease of crops, but the artificial neural network using for predicting cotton boil spoiling disease have not been seen yet. Xinxiang is a city of Henan province of china, according to the survey materials of 10 years, the high output cotton boil spoiling disease break out every 4 years, the average quantity is 1.53, the rate of boil spoiling disease is 11.84%, so the loss is 168.28 . In order to prevent the cotton boil spoiling disease, we should forecast the disease, by doing this, it can increase quantity and quality of the cotton.

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