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Application of probabilistic deep learning models to simulate thermal power plant processes
Deep learning has gained traction in thermal engineering due to its applications to process simulations, the deeper insights it can provide and its abilities to circumvent the shortcomings of classic thermodynamic simulation approaches by capturing complex inter-dependencies. This works sets out to...
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| Format: | Thesis |
| Language: | English |
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Department of Mechanical Engineering
2023
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