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Explore IndustryUsing artificial intelligence to improve your mechatronic system development process
Using artificial intelligence to improve your mechatronic system development process
Using artificial intelligence to improve your mechatronic system development process
Artificial neural networks, a main pillar of many data driven artificial intelligence applications, have been growing in popularity in different domains, from speech recognition over image processing to control tasks with complex sensory inputs and multiple outputs. Mechatronic systems have in the meantime been growing in complexity, requiring a dedicated model-based systems development process to assure the functional and performance design attributes.
In this webinar, the aid of artificial neural networks in mechatronic system development is demonstrated based on examples from the different phases of the development cycle of vehicle systems. The applicability of various types of neural networks (DNN, CNN, RNN, …) is explored for the different engineering tasks: data interpretation, model reduction, automatic controls generation, predictive maintenance and even engineering assistance to designers or analysts.
Peter Mas and Yerlan Akhmetov from Simcenter Engineering Services walk you through:
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Using artificial intelligence to improve your mechatronic system development process
Artificial neural networks, a main pillar of many data driven artificial intelligence applications, have been growing in popularity in different domains, from speech recognition over image processing to control tasks with complex sensory inputs and multiple outputs. Mechatronic systems have in the meantime been growing in complexity, requiring a dedicated model-based systems development process to assure the functional and performance design attributes.
In this webinar, the aid of artificial neural networks in mechatronic system development is demonstrated based on examples from the different phases of the development cycle of vehicle systems. The applicability of various types of neural networks (DNN, CNN, RNN, …) is explored for the different engineering tasks: data interpretation, model reduction, automatic controls generation, predictive maintenance and even engineering assistance to designers or analysts.
Peter Mas and Yerlan Akhmetov from Simcenter Engineering Services walk you through: