A data-driven approach consolidates unstructured disturbances into residual terms estimated from data to yield causal and distributionally consistent stochastic predictors for uncertainty quantification via polynomial chaos expansions and Chebyshev inequalities, validated on Norwegian smart-home实验数据
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Uncertainty Propagation under Residual Disturbances: A Smart-Home Case Study
A data-driven approach consolidates unstructured disturbances into residual terms estimated from data to yield causal and distributionally consistent stochastic predictors for uncertainty quantification via polynomial chaos expansions and Chebyshev inequalities, validated on Norwegian smart-home实验数据