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AUTOMATIC GENERATION A NET OF MODELS FOR HIGH AND LOW LEVELS OF PRODUCTION CONTROL

机译:自动生成生产控制高低层模型的网络

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The paper presents two applications of the novel, artificial neural network (ANN) and feature selection based combined, dynamic technique to automatically dissolve a large, complex system into a net of connected submodels. The first application is a solution for the lower level of customised mass-production systems, for increasing their productivity. The second one is a concept for the identification and reorganisation of manufacturing agents, based on simulation experience. The main idea behind, is to give the learning capability to agents already at their definition phase, and to maximise their foresight power.
机译:本文介绍了新颖的人工神经网络(ANN)和基于特征选择的组合动态技术在自动将大型复杂系统分解为连接的子模型网中的两个应用。第一个应用是针对较低级别的定制量产系统的解决方案,以提高其生产率。第二个概念是根据模拟经验来识别和重组制造代理商的概念。背后的主要思想是为已经处于定义阶段的代理提供学习能力,并最大限度地提高其预测能力。

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