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Machine learning (ML) technologies are emerging in Mechanical Engineering, driven by the increasing availability of datasets, coupled with the exponential growth in computer performance. In fact, there has been a growing interest in evaluating the capabilities of ML algorithms to approach topics related to metal forming processes, such as: Classification, detection and prediction of forming defects; Material parameters identification; Material modelling; Process classification and selection; Process design and optimization. The purpose of this Special Issue is to disseminate state-of-the-art ML applications in metal forming processes, covering 10 papers about the abovementioned and related topics.
| Leidėjas: | MDPI AG |
| Išleidimo metai: | 2022 |
| Knygos puslapių skaičius: | 210 |
| ISBN-10: | 3036557717 |
| ISBN-13: | 9783036557717 |
| Formatas: | 250 x 175 x 18 mm. Knyga kietu viršeliu |
| Kalba: | Anglų |
Parašykite atsiliepimą apie „Recent Advances and Applications of Machine Learning in Metal Forming Processes“
