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Titlebook: Artificial Intelligence in Industrial Decision Making, Control and Automation; Spyros G. Tzafestas,Henk B. Verbruggen Book 1995 Springer S

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Neural Networks in Robot Control nerve cells that have a number of internal parameters called synaptic weights. The human brain consists of over ten million neurons. The weights are adjusted adaptively according to the task under execution such that to improve the overall system performance. Here we are dealing with artificial NNs
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Control Strategy of Robotic Manipulator Based on Flexible Neural Network Structurehe ANNs are a parallel processing artichecture in which a large number of processing neurons are interconnected and the knowledge is represented by the connection weights between the neurons. The connection weights are adjusted through a learning process. The knowlegde is distributed over a large nu
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Neuro-Fuzzy Approaches to Anticipatory Controlustrial processes, global markets, provide many examples of behavior where global output is the result of anticipated not only current state. In the global economy, for example, the anticipation of an oil shortage or of a significant default of foreign loans can have profound effects upon the course
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Krankheiten des venösen Gefäßsystemsknowledge is needed to apply these techniques, in contrast with that which is necessary in the application of symbolic AI techniques based on logic. In symbolic AI systems, the knowledge is represented explicitly, for example by using production rules.
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