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Found 8 papers, 1 papers with code
Regularization methods for the short-term forecasting of the Italian electric load
The problem of forecasting the whole 24 profile of the Italian electric load is addressed as a multitask learning problem, whose complexity is kept under control via alternative regularization methods.
Preemptive periodic epidemic control reduces life and healthcare system costs without aggravation of social and economic losses
Many countries are managing COVID-19 epidemic by switching between lighter and heavier restrictions.
Vaccination and SARS-CoV-2 variants: how much containment is still needed? A quantitative assessment
Despite the progress in medical care, combined population-wide interventions (such as physical distancing, testing and contact tracing) are still crucial to manage the SARS-CoV-2 pandemic, aggravated by the emergence of new highly transmissible variants.
Identification of AC Networks via Online Learning
The increasing penetration of intermittent distributed energy resources in power networks calls for novel planning and control methodologies which hinge on detailed knowledge of the grid.
Ensembling methods for countrywide short term forecasting of gas demand
Gas demand is made of three components: Residential, Industrial, and Thermoelectric Gas Demand.
Forecasting residential gas demand: machine learning approaches and seasonal role of temperature forecasts
On the Italian data, it is shown that temperature forecast errors account for some 18% of the mean squared error of gas demand forecasts provided by ANN.
Fast calibration of two-factor models for energy option pricing
Energy companies need efficient procedures to perform market calibration of stochastic models for commodities.
Pricing of Securities
Regularized linear system identification using atomic, nuclear and kernel-based norms: the role of the stability constraint
In this paper, a comparative study of estimators based on these different types of regularizers is reported.
