Adaptive Systems Control: Difference between revisions
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Most factories today rely on complex networks of disconnected production equipment, leading to inefficiencies in control systems such as temperature control, power usage, and material flow. ML techniques such as image recognition, regression trees, and time delay neural networks can help optimize the control and efficient automation of industrial systems. |
Most factories today rely on complex networks of disconnected production equipment, leading to inefficiencies in control systems such as temperature control, power usage, and material flow. ML techniques such as image recognition, regression trees, and time delay neural networks can help optimize the control and efficient automation of industrial systems. |
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Background Readings |
== Background Readings == |
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Online Courses and Course Materials |
== Online Courses and Course Materials == |
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Data |
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== Data == |
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Latest revision as of 02:07, 23 December 2020
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Most factories today rely on complex networks of disconnected production equipment, leading to inefficiencies in control systems such as temperature control, power usage, and material flow. ML techniques such as image recognition, regression trees, and time delay neural networks can help optimize the control and efficient automation of industrial systems.