Title :
Strategies and issues in applications of neural networks
Author :
Feldkamp, L.A. ; Puskorius, G.V. ; Davis, L.I., Jr. ; Yuan, F.
Author_Institution :
Ford Motor Co., Dearborn, MI, USA
Abstract :
The authors survey some of the fundamental aspects of neural networks that have been found crucial to their application to practical problems in diagnostics, modeling, and control. The analysis is a loosely connected collection of remarks on difficulties that have been encountered and the approach to dealing with them. Promising approaches now being explored and suggestions for future work are outlined. The issues raised concern the following: neural nets and engineering; training by higher order methods; sparse data and generalization; local representation networks; prestructured networks; scaling nodes; context switching; recurrent networks; neural controller development; and fusion of neural nets and fuzzy logic
Keywords :
neural nets; context switching; fuzzy logic; generalization; local representation networks; neural controller development; neural nets; neural networks; prestructured networks; recurrent networks; scaling nodes; sparse data; Backpropagation algorithms; Biological neural networks; Biological system modeling; Differential equations; Gradient methods; Intelligent networks; Least squares approximation; Neural networks; Neuroscience; Resonance;
Conference_Titel :
Neural Networks, 1992. IJCNN., International Joint Conference on
Conference_Location :
Baltimore, MD
Print_ISBN :
0-7803-0559-0
DOI :
10.1109/IJCNN.1992.227325
