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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 online resource (362 p.) |
| Soggetto topico |
Mathematics and Science
Research and information: general |
| Soggetto non controllato |
NET framework
adaptive sampling agent algorithms agent-based systems animal-inspired applied machine learning approximate differential optimization autonomous driving class imbalance classification classification and regression combinatorics computational complexity data mining deep learning deep neural networks DeepFKTNet defect classification distance metrics distributed W-learning dynamic programming algorithm engineering informatics ensemble model evolutionary algorithm exploitation exploration free radical polymerization gender-based violence in Mexico generative adversarial networks graph neural network hot rolled strip steel hyperparameters image classification inference instance-based learning intelligent transport systems interoperability k-nearest neighbor knockout tournament large margin nearest neighbor regression machine learning metaheuristics multi-agent framework multi-agent systems multiple point hill climbing multisensory fingerprint n/a object tracking optimization plastic bottle prototypes reinforcement learning simulations software design spatial-temporal variable speed limit stochastic methods surface defects traffic control trajectory prediction transfer learning twitter messages urban motorways |
| 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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Statistical Data Modeling and Machine Learning with Applications
| Statistical Data Modeling and Machine Learning with Applications |
| Autore | Gocheva-Ilieva Snezhana |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 |
| Descrizione fisica | 1 online resource (184 p.) |
| Soggetto topico | Information technology industries |
| Soggetto non controllato |
artificial neural networks
assessment banking brain-computer interface breast cancer subtyping CART ensembles and bagging categorical data citizen science classification classification and regression tree clustering CNN-LSTM architectures consensus models convexity cross-validation dam inflow prediction damped Newton data quality data-adaptive kernel functions deep forest EEG motor imagery ensemble model feature selection Gower's interpolation formula Gower's metric hedonic prices housing hyper-parameter optimization image data input predictor selection kernel clustering kernel density estimation long short-term memory machine learning mathematical competency METABRIC dataset mixed data multi-category classifier multi-omics data multidimensional scaling multivariate adaptive regression splines n/a non-linear optimization predictive models quantile regression real-time motion imagery recognition similarity stochastic gradient descent support vector machine wavelet transform |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557359003321 |
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Gocheva-Ilieva Snezhana
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| Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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