Abstract
This paper deals with a new methodology for the development of an expert system (ES) using a hybrid architecture. This architecture simplifies the knowledge acquisition phase, by providing some sort of learning corresponding to the training phase of the neural network. So, it is possible to start with the nucleus of a knowledge base and the system will improve during the learning phase using examples.
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© 1998 Springer-Verlag Wien
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Brasil, L.M., de Azevedo, F.M., Barreto, J.M. (1998). A Hybrid Expert System Architecture for Medical Diagnosis. In: Artificial Neural Nets and Genetic Algorithms. Springer, Vienna. https://doi.org/10.1007/978-3-7091-6492-1_33
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DOI: https://doi.org/10.1007/978-3-7091-6492-1_33
Publisher Name: Springer, Vienna
Print ISBN: 978-3-211-83087-1
Online ISBN: 978-3-7091-6492-1
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