A neural network based expert system model

A. Hudli, M. Palakal, M. J. Zoran
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引用次数: 2

Abstract

The architecture of an expert system model using artificial neural networks is proposed. The proposed model effectively supports the necessary components of an expert system such as user interface facility knowledge base, inference engine, and explanation system. The expert system model (ESM) consists of several orders of simple neural networks, each realizing a simple task. These simple neural networks are organized vertically, thereby achieving a second level of parallelism. A novel way to handle both forward and backward chaining reasoning mechanisms is presented. A secondary network model monitors the reasoning patterns of the primary model.<>
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基于神经网络的专家系统模型
提出了基于人工神经网络的专家系统模型体系结构。该模型有效地支持了专家系统的必要组成部分,如用户界面设施知识库、推理引擎和解释系统。专家系统模型(ESM)由几阶简单的神经网络组成,每阶神经网络实现一个简单的任务。这些简单的神经网络是垂直组织的,从而达到了第二级并行性。提出了一种处理正向和反向链推理机制的新方法。二级网络模型监视主模型的推理模式。
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