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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 |
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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Probabilistic and Fuzzy Approaches for Estimating the Life Cycle Costs of Buildings
| Probabilistic and Fuzzy Approaches for Estimating the Life Cycle Costs of Buildings |
| Autore | Plebankiewicz Edyta |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 |
| Descrizione fisica | 1 electronic resource (220 p.) |
| Soggetto topico | Technology: general issues |
| Soggetto non controllato |
dynamic analysis
steel frames Tuned Mass Damper optimization drift ratio sustainable construction industry lifecycles European Union Member States complex evaluation multiple criteria analysis COPRAS and INVAR methods success and image of a country marketing residential buildings defects intensity reliability technical wear railway infrastructure occurrences socioeconomic impact economic evaluation CBA life cycle investment project probability distribution sensitivity analyses risk assessment tenement houses damage maintenance fuzzy sets Bayes conditional probability substitution operation and maintenance phase cause–effect relationships historical buildings implementation factors information and communication technology life cycle costs buildings bidding decision LCC criterion price criterion construction statistical method classification probability of winning risk identification MCDM critical risk factors commercial and recreational complex building projects |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557659003321 |
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Plebankiewicz Edyta
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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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