Стохастическая фильтрация в пространстве мнений экспертов
Работая с нашим сайтом, вы даете свое согласие на использование файлов cookie. Это необходимо для нормального функционирования сайта, показа целевой рекламы и анализа трафика. Статистика использования сайта отправляется в «Яндекс» и «Google»
Научный журнал Моделирование, оптимизация и информационные технологииThe scientific journal Modeling, Optimization and Information Technology
Online media
issn 2310-6018

Stochastic filtering in the space of expert opinions

Grechanyi S.A.   idKrivobokova S.E.

UDC 519.254
DOI: 10.26102/2310-6018/2022.36.1.022

  • Abstract
  • List of references
  • About authors

Currently, there are many difficulties associated with the financial aspect that affects the security of the facility when assembling a set of technical security equipment. To solve the problems of the facility safety, and therefore the reliability of individual security devices, it is recommended to involve experts. At the same time, experts’ opinions may not always be infallible. In this study, it is proposed to carry out a stochastic analysis and filtering of the expert opinion space in order to identify a conditional trend (established opinion) of each expert. The main method of researching this issue is the analysis of conditional time series (testing the hypothesis of the trend absence by means of the median method in the sequence of expert assessments), which makes it possible to determine the validity of the method, as well as to ensure experts’ objectivity of assessments. The article presents a step-by-step operation algorithm for empirical data, calculates the average deviations from the trend line, considers two methods for testing the null hypothesis – the median method and Foster–Stewart method. The materials of the article can be applied in various areas of setting the average score since the algorithm for testing the null hypothesis is universal in nature.

1. Krivobokova S., Rodin V. Analysis of expert opinions to reduce the dimensionality of vector optimization in the problem of determining the optimum set of security devices. 3rd International Conference on Control Systems, Mathematical Modeling, Automation and Energy Efficiency (SUMMA). 2021:10–14. DOI: 10.1109/SUMMA53307.2021.

2. Krivobokova S.E., Rodin V.A. Algorithm and program for the graphical selection of the Pareto set in a dotted array. Prikladnaya matematika & Fizika = Applied Mathematics & Physics. 2021:125–131. DOI:10.52575/2687-0959-2021-53-2-125-131. (In Russ.)

3. Krivobokova S.E., Rodin V.A. Optimal equipment of the object with special security equipment based on the generalized Harrinkton indicator. Vestnik Voronezhskogo instituta MVD Rossii = Bulletin of the Voronezh Institute of the Ministry of Internal Affairs of Russia. 2021:154–164. (In Russ.)

4. Lyubushin N.P., Brikach G.E. Use of the generalized Harrinkton desirability function in multiparameter economic problems. Metody analiza = Analysis methods. 2014:1–9. (In Russ.)

5. Men'shikh V.V. Legal statistics: methods and models. Voronezh Institute of the Ministry of Internal Affairs of Russia; 2018. 302 p. (In Russ.)

6. Malykhin V.I., Rodin V.A. Decision making theory. Voronezh: Voronezh State University Publishing House; 2015. 322 p. (In Russ.)

7. Petrovsky A.B. Decision making theory. Moscow: Publishing Center "Academy"; 2009. 400 p. (In Russ.)

8. Kotenko A.P. Econometrics. Time series. Samara: Samara University Publishing House; 2016. 20 p. (In Russ.)

9. Kharchenko M.A. Correlation analysis. Voronezh: Voronezh State University Publishing and Printing Center; 2008. 124 p. (In Russ.)

10. Orlov A.I. Organizational and economic modeling: decision theory. Moscow: KNORUS; 2010. 568 p. (In Russ.)

Grechanyi Sergei Anatolevich
Candidate of Technical Sciences

Voronezh Institute of the Ministry of Internal Affairs of the Russian Federation

Voronezh, Russian Federation

Krivobokova Svetlana Evgenevna

ORCID |

Voronezh Institute of the Ministry of Internal Affairs of the Russian Federation

Voronezh, Russian Federation

Keywords: conditional short time series, stochastic filtering, least square method, regression equation, median method, foster–Stewart method, standard deviation

For citation: Grechanyi S.A. Krivobokova S.E. Stochastic filtering in the space of expert opinions. Modeling, Optimization and Information Technology. 2022;10(1). Available from: https://moitvivt.ru/ru/journal/pdf?id=1121 DOI: 10.26102/2310-6018/2022.36.1.022 (In Russ).

394

Full text in PDF

Received 23.12.2021

Revised 22.01.2022

Accepted 11.03.2022

Published 21.03.2022