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Advances in Condition Monitoring, Optimization and Control for Complex Industrial Processes
| Advances in Condition Monitoring, Optimization and Control for Complex Industrial Processes |
| Autore | Gao Zhiwei |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 |
| Descrizione fisica | 1 electronic resource (514 p.) |
| Soggetto topico | Technology: general issues |
| Soggetto non controllato |
process control
separation oil and gas control chart fuzzy logic neutrosophic statistic incomplete data belief statistic gamma distribution microalgae raceway control problem PID event-based flexible flow shop scheduling multi-queue limited buffers improved compact genetic algorithm probability density function of the Gaussian distribution transfer bees optimizer reinforcement learning behavior transfer state-action chains reactive power optimization Holmquist-Johnson-Cook constitutive model of briquette parameter acquisition split Hopkinson pressure bar experiment numerical simulation pressure swing distillation full-heat integration acetonitrile water distributed model predictive control steam power plant steam/water loop multi-input and multi-output system loop design optimal nonlinear adaptive control memetic salp swarm algorithm voltage source converter perturbation observer hardware experiment MIMO temperature control in heating process system pole-zero cancelation temperature difference transient response dead time slow-mode-based control multi-input multi-output (MIMO) temperature system temperature differences non-pillar gob-side entry retaining by roof cutting close distance coal seams goaf stress distribution semiconductor bonding equipment-grouping method graph theory association matrix CFSFDP algorithm self-learning variable geometry turbocharger deep reinforcement learning deep deterministic policy gradient flexible flow shop limited buffer public buffer Hopfield neural network local scheduling simulated annealing algorithm load identification EWT multiscale fuzzy entropy PNN Hybrid Attack Graph Level-of-Resilience stability topology distributed generation (DG) INSGA-II multi-objective optimization potential crowding distance static and dynamic planning data-driven methods coarse model refrigeration tunnel boring machine roadway supporting constitutive model failure criterion in-situ monitoring power systems complex network theory Fast-Newman algorithm link-addition strategy cascading failures flotation process reagent dosage time series froth image cumulative distribution function fault diagnosis fault classification fast Fourier transform (FFT) multi-linear principal component analysis (MPCA) uncorrelated multi-linear principal component analysis (UMPCA) additive white Gaussian noises (AWGN) wind turbine systems deviation control drilling machine nonlinear adaptive backstepping controller disturbance observer parameter uncertainties wind turbine energy conversion systems condition monitoring fault prognosis resilient control |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557338303321 |
Gao Zhiwei
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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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Computational Intelligence for Modeling, Control, Optimization, Forecasting and Diagnostics in Photovoltaic Applications
| Computational Intelligence for Modeling, Control, Optimization, Forecasting and Diagnostics in Photovoltaic Applications |
| Autore | Vitelli Massimo |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020 |
| Descrizione fisica | 1 electronic resource (280 p.) |
| Soggetto topico | History of engineering & technology |
| Soggetto non controllato |
sensor network
data fusion complex network analysis fault prognosis photovoltaic plants ANFIS statistical method gradient descent photovoltaic system sustainable development PV power prediction artificial neural network renewable energy environmental parameters multiple regression model moth-flame optimization parameter extraction photovoltaic model double flames generation (DFG) strategy Solar cell parameters single-diode model two-diode model COA photovoltaic systems maximum power point tracking single stage grid connected systems solar concentrator spectral beam splitting diffractive optical element diffractive grating PVs power output forecasting adaptive neuro-fuzzy inference systems particle swarm optimization-artificial neural networks solar irradiation photovoltaic power prediction publicly available weather reports machine learning long short-term memory integrated energy systems smart energy management PV fleet clustering-based PV fault detection unsupervised learning self-imputation implicit model solution photovoltaic array series–parallel global optimization partial shading deterministic optimization algorithm metaheuristic optimization algorithm genetic algorithm solar cell optimization finite difference time domain optical modelling thermal image photovoltaic module hot spot image processing deterioration linear approximation MPPT algorithm duty cycle global horizontal irradiance mathematical modeling feed-forward neural networks recurrent neural networks LSTM cell performances evaluation clear sky irradiance persistent predictor photovoltaics artificial neural networks national power system |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557297703321 |
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Vitelli Massimo
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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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