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

机译:自动生成高低水平的模型网

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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:本文提出了两种应用的新颖,人工神经网络(ANN)和特征选择的组合,动态技术将大型复杂系统自动溶解成连接的子模型的网络。第一申请是用于较低的定制大规模生产系统的解决方案,以提高其生产率。第二个是基于模拟经验的制造代理的识别和重组的概念。背后的主要观点是将学习能力与已经在定义阶段进行了学习能力,并最大限度地提高了他们的远见权力。

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