Entropy-Randomized Forecasting of Stochastic Dynamic Regression Models

Yuri S. Popkov, Alexey Yu. Popkov, Yuri A. Dubnov and Dimitri Solomatine
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Yuri S. Popkov: Federal Research Center “Computer Science and Control” of Russian Academy of Sciences, Moscow 119333, Russia
Alexey Yu. Popkov: Federal Research Center “Computer Science and Control” of Russian Academy of Sciences, Moscow 119333, Russia
Yuri A. Dubnov: Federal Research Center “Computer Science and Control” of Russian Academy of Sciences, Moscow 119333, Russia
Dimitri Solomatine: IHE Delft Institute for Water Education, 2601 Delft, The Netherlands

Mathematics, 2020, vol. 8, issue 7, 1-20

Abstract: We propose a new forecasting procedure that includes randomized hierarchical dynamic regression models with random parameters, measurement noises and random input. We developed the technology of entropy-randomized machine learning, which includes the estimation of characteristics of a dynamic regression model and its testing by generating ensembles of predicted trajectories through the sampling of the entropy-optimal probability density functions of the model parameters and measurement noises. The density functions are determined at the learning stage by solving the constrained maximization problem of an information entropy functional subject to the empirical balances with real data. The proposed procedure is applied to the randomized forecasting of the daily electrical load in a regional power system. We construct a two-layer dynamic model of the daily electrical load. One of the layers describes the dependence of electrical load on ambient temperature while the other simulates the stochastic quasi-fluctuating temperature dynamics.

Keywords: forecasting; randomization; dynamic regression; information entropy; empirical balance; randomized machine learning (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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