Bayesian recognition of a moving object information-measuring system state: a priori information weight correction

S. M. Muzhichek, G. G. Sebryakov, V I Pavlov, S V Tolstych, M B Kenzhekhanova

2021

Full text Open access: Gold Metadata (CSL-JSON)

DOI 10.1088/1757-899x/1027/1/012021

Data confidence 70 medium

How this score is calculated

It is built from checkable properties of the record itself: whether the article has a DOI, how many independent sources confirmed its data, whether the required fields are filled in, and how recent the latest confirmation is. Disagreement between sources and a missing identifier lower it. A value of 80 or above means the record was published without further checking; 60 to 79 means it is published at reduced confidence, with a manual check advisable. A record verified by an editor by hand is never pushed below 90 by a recalculation. This scores our data about the article, not the article itself.

Abstract

Abstract Within the framework of the Bayesian approach, a method has been developed for recognizing signal-interference situations that arise during the operation of the information-measuring system of a moving object. The corresponding algorithms are presented. A method for correcting the weight of a priori information in the case of its significant difference from a posteriori information is proposed. One of the possible correction options using the so-called indicators of signals and interference accompanying signs is presented.