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Short-Term Load Forecasting 2019
| Short-Term Load Forecasting 2019 |
| Autore | Gabaldón Antonio |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 |
| Descrizione fisica | 1 electronic resource (324 p.) |
| Soggetto topico | History of engineering & technology |
| Soggetto non controllato |
short-term load forecasting
demand-side management pattern similarity hierarchical short-term load forecasting feature selection weather station selection load forecasting special days regressive models electric load forecasting data preprocessing technique multiobjective optimization algorithm combined model Nordic electricity market electricity demand component estimation method univariate and multivariate time series analysis modeling and forecasting deep learning wavenet long short-term memory demand response hybrid energy system data augmentation convolution neural network residential load forecasting forecasting time series cubic splines real-time electricity load seasonal patterns Load forecasting VSTLF bus load forecasting DBN PSR distributed energy resources prosumers building electric energy consumption forecasting cold-start problem transfer learning multivariate random forests random forest electricity consumption lasso Tikhonov regularization load metering preliminary load short term load forecasting performance criteria power systems cost analysis day ahead feature extraction deep residual neural network multiple sources electricity |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557494303321 |
Gabaldón Antonio
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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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Short-Term Load Forecasting by Artificial Intelligent Technologies
| Short-Term Load Forecasting by Artificial Intelligent Technologies |
| Autore | Wei-Chiang Hong (Ed.) |
| Pubbl/distr/stampa | MDPI - Multidisciplinary Digital Publishing Institute, 2019 |
| Descrizione fisica | 1 electronic resource (444 p.) |
| Soggetto non controllato |
meta-heuristic algorithms
artificial neural networks (ANNs) knowledge-based expert systems statistical forecasting models evolutionary algorithms short term load forecasting novel intelligent technologies support vector regression/support vector machines seasonal mechanism |
| ISBN | 3-03897-583-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910346838403321 |
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Wei-Chiang Hong (Ed.)
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| MDPI - Multidisciplinary Digital Publishing Institute, 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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