2021
DOI: 10.15587/1729-4061.2021.244623
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Investigating errors when forecasting processes with uncertain dynamics and observation noise by the self-adjusting brown's zero-order model

Abstract: This paper reports a study into the errors of process forecasting under the conditions of uncertainty in the dynamics and observation noise using a self-adjusting Brown's zero-order model. The dynamics test models have been built for predicted processes and observation noises, which make it possible to investigate forecasting errors for the self-adjusting and adaptive models. The test process dynamics were determined in the form of a rectangular video pulse with a fixed unit amplitude, a radio pulse of the har… Show more

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Cited by 1 publication
(2 citation statements)
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“…This is due to the different purposes of the methods. To identify dangerous air pollution, in [43], it is proposed to use the uncertainty function for pollution. However, the STF method with UD is not considered in works [42,43].…”
Section: Literature Review and Problem Statementmentioning
confidence: 99%
See 1 more Smart Citation
“…This is due to the different purposes of the methods. To identify dangerous air pollution, in [43], it is proposed to use the uncertainty function for pollution. However, the STF method with UD is not considered in works [42,43].…”
Section: Literature Review and Problem Statementmentioning
confidence: 99%
“…To identify dangerous air pollution, in [43], it is proposed to use the uncertainty function for pollution. However, the STF method with UD is not considered in works [42,43]. In [44], the accuracy of HP STF based on ZOBM is investigated.…”
Section: Literature Review and Problem Statementmentioning
confidence: 99%