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Machine Learning, Low-Rank Approximations and Reduced Order Modeling in Computational Mechanics / Felix Fritzen, David Ryckelynck
| Machine Learning, Low-Rank Approximations and Reduced Order Modeling in Computational Mechanics / Felix Fritzen, David Ryckelynck |
| Autore | Fritzen Felix |
| Pubbl/distr/stampa | MDPI - Multidisciplinary Digital Publishing Institute, 2019 |
| Descrizione fisica | 1 electronic resource (254 p.) |
| Soggetto topico | History of engineering and technology |
| Soggetto non controllato |
supervised machine learning
proper orthogonal decomposition (POD) PGD compression stabilization nonlinear reduced order model gappy POD symplectic model order reduction neural network snapshot proper orthogonal decomposition 3D reconstruction microstructure property linkage nonlinear material behaviour proper orthogonal decomposition reduced basis ECSW geometric nonlinearity POD model order reduction elasto-viscoplasticity sampling surrogate modeling model reduction enhanced POD archive modal analysis low-rank approximation computational homogenization artificial neural networks unsupervised machine learning large strain reduced-order model proper generalised decomposition (PGD) a priori enrichment elastoviscoplastic behavior error indicator computational homogenisation empirical cubature method nonlinear structural mechanics reduced integration domain model order reduction (MOR) structure preservation of symplecticity heterogeneous data reduced order modeling (ROM) parameter-dependent model data science Hencky strain dynamic extrapolation tensor-train decomposition hyper-reduction empirical cubature randomised SVD machine learning inverse problem plasticity proper symplectic decomposition (PSD) finite deformation Hamiltonian system DEIM GNAT |
| ISBN |
9783039214105
3039214101 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910367759403321 |
Fritzen Felix
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| MDPI - Multidisciplinary Digital Publishing Institute, 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Numerical and Evolutionary Optimization 2020
| Numerical and Evolutionary Optimization 2020 |
| Autore | Quiroz Marcela |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 |
| Descrizione fisica | 1 online resource (364 p.) |
| Soggetto topico |
Mathematics & science
Research & information: general |
| Soggetto non controllato |
adaptive algorithm
artificial intelligence base excitation chaotic perturbation CMOS differential pair CMOSA CMOTA cognitive tasks computational fluid dynamics constraint handling continuation Convolutional Neural Network COVID-19 decision maker profile decision making process decision-making process deep learning density estimators derivative-free optimization differential evolution drainage rehabilitation energy central ensemble method evolutionary algorithms finite volume method fixed point arithmetic forecasting FP16 fully linear models hybrid evolutionary approach Hybrid Simulated Annealing incorporation of preferences JSSP kriging method linear programming liquid storage tanks LSTM Metropolis Monte Carlo analysis multi-criteria classification Multi-Gene Genetic Programming multi-objective evolutionary optimization multi-objective optimization multi-objective portfolio optimization problem multiobjective descent multiobjective optimization optimization optimization framework optimization using preferences outranking relationships overflooding Pareto Tracer pipe breaking profile assessment project portfolio selection problem protein structure prediction pseudo random number generator PVT variations radial basis functions recommender system region of interest approximation robust optimization ROOT steady state algorithms structural biology surrogate modeling Template-Based Modeling trapezoidal fuzzy numbers trust region methods usability evaluation VCO |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557631003321 |
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Quiroz Marcela
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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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Wildfire Hazard and Risk Assessment
| Wildfire Hazard and Risk Assessment |
| Autore | Meldrum James R |
| Pubbl/distr/stampa | Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 |
| Descrizione fisica | 1 online resource (222 p.) |
| Soggetto topico |
Biology, life sciences
Forestry & related industries Research & information: general |
| Soggetto non controllato |
area difference index
colour coding communication community vulnerability defensible space disaster erosion fire fire behavior fire hazard fire spread model fire spread models fire suppression costs firefighter safety flammap forest fire fuels GEDI global sensitivity analysis Google Earth Engine land use LANDFIRE Landsat LCES lidar LiDAR mapping mitigation modeling Monte Carlo Monte Carlo simulation natural hazards object-oriented image analysis ordinal categorization palette parcel-level risk post-fire analysis Potential fire Operational Delineations precision predictive modeling prescribed fire principal components analysis rapid assessment recall remote sensing risk risk assessment risk mitigation safe separation distance safety zones sensitivity analysis Sentinel Sentinel-2 simulation spatial modeling statistics structure loss surrogate modeling transmission risk water supply wildfire wildfire containment wildfire management wildfire risk wildland-urban interface WUI Zillow |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910566472703321 |
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Meldrum James R
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| Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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