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Found 4 papers, 0 papers with code
On-line conformalized neural networks ensembles for probabilistic forecasting of day-ahead electricity prices
Probabilistic electricity price forecasting (PEPF) is subject of increasing interest, following the demand for proper quantification of prediction uncertainty, to support the operation in complex power markets with increasing share of renewable generation.
Probabilistic electric load forecasting through Bayesian Mixture Density Networks
Probabilistic load forecasting (PLF) is a key component in the extended tool-chain required for efficient management of smart energy grids.
Identification of Probability weighted ARX models with arbitrary domains
Hybrid system identification is a key tool to achieve reliable models of Cyber-Physical Systems from data.
Estimation of Switched Markov Polynomial NARX models
This work targets the identification of a class of models for hybrid dynamical systems characterized by nonlinear autoregressive exogenous (NARX) components, with finite-dimensional polynomial expansions, and by a Markovian switching mechanism.
