This article is cited in 5 papers

Measurement reduction in the presence of subjective information

D. A. Balakin, Yu. P. Pyt'ev

Lomonosov Moscow State University, Faculty of Physics

Abstract: The article considers an application of the mathematical formalism of subjective modeling to improve the quality of measurement data interpretation by using a researcher's incomplete and unreliable subjective information about the research object. It is shown the mathematical formalism of subjective modeling allows the researcher to use measurement data to test the adequacy of the subjective model for the research objective, to correct the subjective model, to combine the observation data and his subjective notions about the research object to optimize his conclusions about the researched features of the research object and how to check the information about the research object for misinformation. Obtained results are illustrated by computer experiments.

Keywords: measurement reduction, subjective modeling, information fusion, information verification.

Received: 07.09.2017

 English version: Mathematical Models and Computer Simulations, 2019, 11:4, 596–610