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Learning Markov models of fading channels in wireless control networks: a regression trees based approach
Finite-state Markov models are widely used for modeling wireless channels affected by a variety of non-idealities, ranging from shadowing to interference.
NeurOpt: Neural network based optimization for building energy management and climate control
Model predictive control (MPC) can provide significant energy cost savings in building operations in the form of energy-efficient control with better occupant comfort, lower peak demand charges, and risk-free participation in demand response.
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