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Computer networks design using hybrid fuzzy expert systems

机译:使用混合模糊专家系统的计算机网络设计

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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.
机译:设计和配置大型计算机网络以支持各种应用程序和计算环境是困难的,因为它不仅需要高度专业的技术技能和知识,而且还需要对动态商业市场有深刻的理解。混合模糊专家系统集成了模糊专家系统和神经网络方法,取代了传统的硬决策方法,并提供了比传统技术更好的性能。在本文中,我们提出了一种集成的模糊专家系统,机器学习和神经网络方法来进行大型结构化计算机网络的设计和评估。在介绍了系统概述和主要的研究选择之后,我们详细描述了系统的模块并提供了其潜在用途的示例。

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