Predicting LDC debt rescheduling: performance evaluation of OLS, logit, and neural network models

2001 ◽  
Vol 20 (8) ◽  
pp. 603-615 ◽  
Author(s):  
Douglas K. Barney ◽  
Janardhanan A. Alse
Keyword(s):  
Neural Network ◽  
Performance Evaluation ◽  
Network Models ◽  
Neural Network Models ◽  
Debt Rescheduling

scholarly journals A Performance evaluation of neural network models in traffic volume forecasting

1998 ◽  
Vol 27 (9-11) ◽  
pp. 293-310 ◽  
Author(s):  
S.-Y. Yun ◽  
S. Namkoong ◽  
J.-H. Rho ◽  
S.-W. Shin ◽  
J.-U. Choi
Keyword(s):  
Neural Network ◽  
Performance Evaluation ◽  
Network Models ◽  
Traffic Volume ◽  
Neural Network Models ◽  
A Performance

Method of complex copper-zinc ore typification using neural network models

2020 ◽  
Vol 5 ◽  
pp. 140-147 ◽  
Author(s):  
T.N. Aleksandrova ◽  
◽  
E.K. Ushakov ◽  
A.V. Orlova ◽  
◽  
...  
Keyword(s):  
Neural Network ◽  
Network Models ◽  
Neural Network Models ◽  
Copper Zinc ◽  
Complex Copper

Digital twin of equipment as a basis for the consumer in digital production

2020 ◽  
Keyword(s):  
Neural Network ◽  
Tool Wear ◽  
Chip Formation ◽  
Network Models ◽  
Machining Accuracy ◽  
Neural Network Models ◽  
Digital Twin ◽  
The Neural Network ◽  
Digital Production ◽  
Cyberphysical System

The neural network models series used in the development of an aggregated digital twin of equipment as a cyber-physical system are presented. The twins of machining accuracy, chip formation and tool wear are examined in detail. On their basis, systems for stabilization of the chip formation process during cutting and diagnose of the cutting too wear are developed. Keywords cyberphysical system; neural network model of equipment; big data, digital twin of the chip formation; digital twin of the tool wear; digital twin of nanostructured coating choice

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