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Synergy of artificial neural networks and knowledge-based expert systems for intelligent FMS scheduling

机译:用于智能FMS调度的人工神经网络和知识专家系统的协同作用

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A hybrid architecture that integrates artificial neural networks and knowledge-based expert systems to generate solutions for the real-time scheduling of flexible manufacturing systems is described. The artificial neural networks perform pattern recognition and, due to their inherent characteristics, support the implementation of automated knowledge acquisition and refinement schemes through a feedback mechanism. The artificial neural network structures enable the system to recognize patterns in the tasks to be solved in order to select the best scheduling rule according to different demands. The knowledge-based expert systems are the higher-order elements which drive the inference strategy and interpret the constraints and restrictions imposed by the upper levels of the flexible manufacturing system control hierarchy. The level of self-organization achieved provides a system with a higher probability of success than traditional approaches.
机译:描述了一种混合架构,其集成了人工神经网络和基于知识的专家系统来生成用于为柔性制造系统的实时调度来生成解决方案。人工神经网络执行模式识别,并且由于其固有的特性,通过反馈机制支持实现自动知识获取和细化方案的实现。人工神经网络结构使系统能够识别要解决的任务中的模式,以便根据不同的要求选择最佳调度规则。基于知识的专家系统是推动策略的高阶元素,并解释灵活制造系统控制层次结构的上层施加的约束和限制。实现的自组织水平提供了一个具有比传统方法更高的成功概率的系统。

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