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Advances in Artificial Intelligence: Models, Optimization, and Machine Learning
| Advances in Artificial Intelligence: Models, Optimization, and Machine Learning |
| Autore | Leon Florin |
| Pubbl/distr/stampa | Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 |
| Descrizione fisica | 1 electronic resource (362 p.) |
| Soggetto topico |
Research & information: general
Mathematics & science |
| Soggetto non controllato |
large margin nearest neighbor regression
distance metrics prototypes evolutionary algorithm approximate differential optimization multiple point hill climbing adaptive sampling free radical polymerization autonomous driving object tracking trajectory prediction deep neural networks stochastic methods applied machine learning classification and regression data mining ensemble model engineering informatics gender-based violence in Mexico twitter messages class imbalance k-nearest neighbor instance-based learning graph neural network deep learning hyperparameters machine learning optimization inference metaheuristics animal-inspired exploration exploitation hot rolled strip steel surface defects defect classification knockout tournament dynamic programming algorithm computational complexity combinatorics intelligent transport systems traffic control spatial-temporal variable speed limit multi-agent systems reinforcement learning distributed W-learning urban motorways multi-agent framework NET framework simulations agent-based systems agent algorithms software design multisensory fingerprint interoperability DeepFKTNet classification generative adversarial networks image classification transfer learning plastic bottle |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Altri titoli varianti | Advances in Artificial Intelligence |
| Record Nr. | UNINA-9910580212403321 |
Leon Florin
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| Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Recent Advances and Applications of Machine Learning in Metal Forming Processes
| Recent Advances and Applications of Machine Learning in Metal Forming Processes |
| Autore | Prates Pedro |
| Pubbl/distr/stampa | Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 |
| Descrizione fisica | 1 electronic resource (210 p.) |
| Soggetto topico |
Technology: general issues
History of engineering & technology Mining technology & engineering |
| Soggetto non controllato |
sheet metal forming
uncertainty analysis metamodeling machine learning hot rolling strip edge defects intelligent recognition convolutional neural networks deep-drawing kriging metamodeling multi-objective optimization FE (Finite Element) AutoForm robust analysis defect prediction mechanical properties prediction high-dimensional data feature selection maximum information coefficient complex network clustering ring rolling process energy estimation metal forming thermo-mechanical FEM analysis artificial neural network aluminum alloy mechanical property UTS topological optimization artificial neural networks (ANN) machine learning (ML) press-brake bending air-bending three-point bending test sheet metal buckling instability oil canning artificial intelligence convolution neural network hot rolled strip steel defect classification generative adversarial network attention mechanism deep learning mechanical constitutive model finite element analysis plasticity parameter identification full-field measurements |
| ISBN | 3-0365-5772-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910637782503321 |
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Prates Pedro
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| Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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