Title :
Some problems of building and learning of neural networks while creating user´s expert systems
Author :
Atamanchuk, Z.M. ; Petrov, A.A.
Author_Institution :
JV Neuroma, Moscow, Russia
Abstract :
An experimental confirmation has been obtained of the possibility of neural network expert systems based on learning that uses examples without using any rules of logical deduction. This approach is used in the environment NEXSY, which provides users with the means for expert system creation by themselves. It has been possible to learn the fields of optimal use of algorithms and regimes of neural network learning, presented in NEXSY, and to formulate the rules for choice while building expert systems. It has also been possible to work out a comfortable user interface in NEXSY, permitting successful use of this environment for the practical building of expert systems, and for choosing the optimal paradigm and learning regime according to the conditions of the problem to be solved
Keywords :
expert systems; learning by example; neural nets; user interfaces; NEXSY; learning by example; learning regime; neural network expert systems; optimal algorithm use; optimal paradigm; user interface; Artificial neural networks; Computer architecture; Expert systems; Extrapolation; Logic functions; Neural networks; Real time systems; Recurrent neural networks;
Conference_Titel :
Neuroinformatics and Neurocomputers, 1992., RNNS/IEEE Symposium on
Conference_Location :
Rostov-on-Don
Print_ISBN :
0-7803-0809-3
DOI :
10.1109/RNNS.1992.268625