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CALVIN ENGR 315 - Neural Networks Presentation

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Neural NetworksWhat Are They?Neural Network DiagramTranslation – Input Stimuli to Output ResponseLearning CapabilityControl System ApplicationsAircraft – Flight Control SystemManufacturing Plant – Hot Dip Galvanized Steel StripPower Plant – Utility BoilersNeural NetworksSarah EzzellEngr. 315What Are They?Information processing system (non-algorithmic, non-digital)Inspired by the human brainMade of artificial neurons (neurodes)–Crude approximation of biological neurons–Connected by weights over which signals travel–Arranged in layersNeural Network DiagramInput LayerMiddle LayerOutput LayerInput SignalsOutput SignalsNeurodeConnection LinkTranslation – Input Stimuli to Output Response3 steps–Neurode computes net weighted input received–Converts net input into an activation level–Converts activation level into output signalLearning CapabilityLearns to solve problems, not just programmedLearning achieved by modifying weightsTraining methods–Supervised–Graded–UnsupervisedControl System ApplicationsAircraftManufacturing plantPower plantAircraft – Flight Control SystemNeural network like a human, but better–Adapts like human, only quicker and more accuratelyBack propagation vs. on line learningNetwork integrated with current flight control systems–Removes “gain scheduling”Manufacturing Plant – Hot Dip Galvanized Steel StripManually controlled coating thickness controlsNeural network control model–Developed by Siemens and Thyssen Stahl–Cost-effective, better quality product–On line learningEliminates need for hot measuring equipmentPower Plant – Utility BoilersAir pollutants from power plantsNeuSIGHT system–Used in coal-fired electric power plants–Provides real time closed-loop supervisory control–Improves operating efficiency & reduces


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CALVIN ENGR 315 - Neural Networks Presentation

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