scholarly journals A study of using grey system theory and artificial neural network on the climbing ability of <i>Buergeria robusta</i> frog

2013 ◽  
Vol 03 (02) ◽  
pp. 83-93 ◽  
Author(s):  
Yuan-Hsiou Chang ◽  
Tsai-Fu Chuang
Keyword(s):  
Neural Network ◽  
System Theory ◽  
Artificial Neural Network ◽  
Grey System Theory ◽  
Grey System ◽  
Climbing Ability ◽  
Artificial Neural

Study on Deformation Prediction of Landslide Based on Grey Theory and BP Neural Network

2012 ◽  
Vol 204-208 ◽  
pp. 520-525 ◽  
Author(s):  
Rong Yu Li ◽  
Yong Fen Ruan ◽  
Shi Sheng Li ◽  
Yong Hong Wu
Keyword(s):  
Neural Network ◽  
System Theory ◽  
Bp Neural Network ◽  
Theory Model ◽  
Grey System Theory ◽  
Practical Significance ◽  
Grey Theory ◽  
Grey System ◽  
Engineering Project ◽  
Landslide Deformation

The stability of the landslide can be effectively evaluated and predicted by predicting the future development of landslide deformation according to the actual deformation of the landslide. Therefore, the accuracy of the prediction regarding the landslide deformation determines the validity of the landslide stability assessment. The GM (1.1) model in the grey system theory, uses displacement time series to establish the grey differential equation. By solving the equation, we can obtain a time response function, which can then be used to predict the landslide deformation. The BP neural network is a used for training and exercising on the deformed samples. After the error meets the requirement, we can then use the trained model to predict the landslide deformation. This paper use both grey system theory model and BP neural network model to predict Jinlong ditch application field landslide deformation.The prediction results are compared and analyzed to test the accuracy of these two predictions. Finding a more accurate prediction method for application in actual engineering project has practical significance.

Autofluorescence spectroscopy of oral leukoplakia using an artificial neural network

2000 ◽  
Vol 25 (4) ◽  
pp. 325-325
Author(s):  
J.L.N. Roodenburg ◽  
H.J. Van Staveren ◽  
N.L.P. Van Veen ◽  
O.C. Speelman ◽  
J.M. Nauta ◽  
...  
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Oral Leukoplakia ◽  
Autofluorescence Spectroscopy ◽  
Artificial Neural

1902: Is Steinstrasse After ESWL of Renal Stones Predictable? Artificial Neural Network Analysis

2004 ◽  
Vol 171 (4S) ◽  
pp. 502-503
Author(s):  
Mohamed A. Gomha ◽  
Khaled Z. Sheir ◽  
Saeed Showky ◽  
Khaled Madbouly ◽  
Emad Elsobky ◽  
...  
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Network Analysis ◽  
Renal Stones ◽  
Neural Network Analysis ◽  
Artificial Neural Network Analysis ◽  
Artificial Neural
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