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Found 5 papers, 0 papers with code
The energy revolution: cyber physical advances and opportunities for smart local energy systems
SLES are often developed for a specific range of use cases and functions, and these match the specific requirements and needs of the community, location or site under consideration.
Incorporating forecasting and peer-to-peer negotiation frameworks into a distributed model predictive control approach for meshed electric networks
We propose a novel holistic approach to energy trading composed of a distributed predictive control framework to handle physical interactions, i, e., voltage constraints and power dispatch, together with a negotiation framework to determine pricing policies for energy transactions.
Differential radial basis function network for sequence modelling
We propose a differential radial basis function (RBF) network termed RBF-DiffNet -- whose hidden layer blocks are partial differential equations (PDEs) linear in terms of the RBF -- to make the baseline RBF network robust to noise in sequential data.
Reinforcement Learning-based Thermal Comfort Control for Vehicle Cabins
Vehicle climate control systems aim to keep passengers thermally comfortable.
Linear classifier design under heteroscedasticity in Linear Discriminant Analysis
Under normality and homoscedasticity assumptions, Linear Discriminant Analysis (LDA) is known to be optimal in terms of minimising the Bayes error for binary classification.
