Conference Contribution

Receding Horizon Prediction by Bayesian Combination of Multiple Predictors

Fredrik Ståhl, Rolf Johansson


This paper presents a novel online approach of merging multiple different predictors of time-varying dynamics into a single optimized prediction. Different predictors are merged by recursive weighting into a single prediction using regularized optimization. The approach is evaluated on two different cases of data with shifting dynamics; one example of prediction using several approximate models of a linear system and one case of glucose prediction on a non-linear physiologically based simulated type I diabetes data using several parallel linear predictors. The performance of the combined prediction significantly reduced the total prediction error compared to each
predictor in each example.

In 51st IEEE Conference on Decision and Control, Maui, Hawaii, USA, December 2012.

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