Abstract
Designing and configuring large computer networks to support a variety of applications and computational environments is difficult, as it not only requires highly specialized technical skills and knowledge, but also a deep understanding of a dynamic commercial market. Hybrid fuzzy expert systems integrate fuzzy expert systems and neural networks methods replacing classical hard decision methods and providing better performance than traditional techniques. In this paper, we present an integrated fuzzy expert system, machine learning, and neural networks approach to large structured computer networks design and evaluation. After presenting an overview of the system and the major research choices, we describe in detail the system's modules and present examples of its potential use.
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