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Advanced Sensing and Control for Connected and Automated Vehicles
| Advanced Sensing and Control for Connected and Automated Vehicles |
| Autore | Huang Chao |
| Pubbl/distr/stampa | Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 |
| Descrizione fisica | 1 online resource (284 p.) |
| Soggetto topico |
History of engineering & technology
Technology: general issues |
| Soggetto non controllato |
analytic hierarchy architecture
articulated cargo trucks artificial neural networks attention attention feature fusion autonomous driving autonomous vehicle autonomous vehicles collision warning system connected and autonomous vehicles data-driven dead reckoning electric vehicle electroencephalogram end-to-end learning executive control fronto-parietal network in-vehicle network kabsch algorithm kalman filter model predictive control multi-scale channel attention multi-task learning multiple-model n/a object detection object vehicle estimation off-tracking path planning potential field radar accuracy radar latency real-time control roll stability sigmoid curve simulated driving simulation string stability task-cuing experiment time to collision traffic scenes trajectory tracking TROOP truck platooning tyre blow-out ultra-wideband unified chassis control Unscented Kalman Filter unsprung mass urban platooning urban vehicle platooning V2V communication vehicle dynamic parameters vehicle dynamics model vehicle-to-vehicle communication weighted interpolation yaw stability |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910566481403321 |
Huang Chao
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| Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Advances in Hydrologic Forecasts and Water Resources Management
| Advances in Hydrologic Forecasts and Water Resources Management |
| Autore | Chang Fi-John |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020 |
| Descrizione fisica | 1 online resource (272 p.) |
| Soggetto topico | Research and information: general |
| Soggetto non controllato |
artificial intelligence
artificial neural networks cascade hydropower reservoirs cascade reservoirs changing environments climate change impacts coupled models dammed lake data synthesis data-scarce deglaciating river basin degree of balance and approach elastic-ball modification elasticity coefficient empirical mode decomposition feasible search space flood control flood risk flood-risk map forecast evaluation generalized likelihood uncertainty estimation Generalized Likelihood Uncertainty Estimation (GLUE) GloFAS-Seasonal GR4J model gravitational search algorithm grey entropy method highly urbanized area Hushan reservoir hydrodynamic modelling hydrologic forecasting impoundment operation Internet of Things (IoT) interval number landslide loss-benefit ratio of ecology and power generation machine learning machine learning model Mahalanobis-Taguchi System multi-objective optimal operation model multi-objective optimization multi-objective reservoir operation NDVI opposition learning parameter uncertainty Pareto-front optimal solution set partial mutation probabilistic forecast random forest recurrent nonlinear autoregressive with exogenous inputs (RNARX) regional flood inundation depth risk Sequential Gaussian Simulation signal-to-noise ratio small and medium-scale rivers Snowmelt Runoff Model Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) temporal transferability Three Gorges Reservoir time-varying parameter TOPSIS uncertainty uncertainty analysis Unscented Kalman Filter urban hydrological model urban stormwater water resources management western China whole region perspective Yangtze River Yarlung Zangbo River |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557110703321 |
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Chang Fi-John
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| Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Feasible, Robust and Reliable Automation and Control for Autonomous Systems
| Feasible, Robust and Reliable Automation and Control for Autonomous Systems |
| Autore | Hamid Umar Zakir Abdul |
| Pubbl/distr/stampa | MDPI - Multidisciplinary Digital Publishing Institute, 2022 |
| Descrizione fisica | 1 online resource (232 p.) |
| Soggetto topico |
History of engineering and technology
Technology: general issues |
| Soggetto non controllato |
active learning
ADAS/AD functions advanced driver-assistance system anti-windup artificial intelligence automata learning automated vehicles autonomous driving autonomous vehicle C-ITS cruise control electric vehicle (EV) error weight superposition fault tolerance formal methods generalized Newton-Raphson identification implementations inertial parameters infrastructure assistance interface design IVIM Kalman filtering lane keeping control (LKC) LPV approach Maglev model-based engineering n/a neural networks neuron PID non-smooth finite-time control nonlinear model prediction controller ODD-based AD function design omnidirectional mobile robot outdoor field test passenger comfort path following path planning path tracking previewed tracking reconfigurable control recursive least square with exponential forgetting robust control routing recommendations semi-active suspension control software architecture spline approximation splines trajectory tracking unmanned tracked vehicle unmanned vehicle Unscented Kalman Filter vehicle following vehicle-terrain interaction |
| ISBN | 3-0365-5076-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910619469203321 |
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Hamid Umar Zakir Abdul
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| MDPI - Multidisciplinary Digital Publishing Institute, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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