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Prediction Intervals

A prediction interval is an estimate of an interval in which a future observation will fall, with a certain probability, given what has already been observed. Prediction intervals are often used in regression analysis.

Papers

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Showing 101–110 of 309 papers

TitleStatusHype
Computation of Ultra-Short-Term Prediction Intervals of the Power Prosumption in Active Distribution Networks—0
Context-Based Echo State Networks with Prediction Confidence for Human-Robot Shared Control—0
Adaptive, Distribution-Free Prediction Intervals for Deep Networks—0
Crop yield probability density forecasting via quantile random forest and Epanechnikov Kernel function—0
Accurate and Reliable Forecasting using Stochastic Differential Equations—0
Data-Driven Personalized Energy Consumption Range Estimation for Plug-in Hybrid Electric Vehicles in Urban Traffic—0
Data-Driven vs Traditional Approaches to Power Transformer's Top-Oil Temperature Estimation—0
Distribution-free risk assessment of regression-based machine learning algorithms—0
Efficiency of conformalized ridge regression—0
Conformal Prediction for Electricity Price Forecasting in the Day-Ahead and Real-Time Balancing Market—0
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