Skip to Main Content

Modelling and Data Analysis
2020. Vol. 10, no. 3, 69–84
https://doi.org/10.17759/mda.2020100306
ISSN: 2219-3758 / 2311-9454 (online)

Statistical Simulation of the Probability Distribution Kernel and Its Application to Solve the Quantile Optimization Problem with the Bilinear Loss Function

 
Audio is AI-generated
150

, ,

PDF (RUS)
Online translation in english
GS
Information
in Google Scholar
Metrics

Abstract

The article considers a plane quantile optimization problem with a bilinear loss function, which, using suffi cient optimality conditions, is reduced to a linear programming problem. The reduction is based on the use of a polyhedral model of the kernel of the probability distribution of the vector of random parameters. To build this model, an algorithm based on the method of statistical modeling is proposed. A description of the software package for constructing a kernel model for a number of probability distributions of random parameters is given.

General Information

Keywords: quantile optimization, loss function, stochastic programming, kernel of probability distribution, minimax problem

Journal rubric: Optimization Methods

OpenAlex citations: 1

OpenAlex trends: Aerospace, Electronics, Mathematical Modeling, Advanced Data Processing Techniques, Advanced Computational Techniques in Science and Engineering

Information about the work in OpenAlex

Number of citations: 1

Topics

Aerospace, Electronics, Mathematical Modeling

This cluster of papers covers topics related to forest reforestation, including methods for direct seeding, noise reduction in manufacturing and repair workshops, chip design verification, hydraulic systems management, and seed grading optimization. It also explores environmental impact assessment, vibroacoustic characteristics research, and quality management systems in the context of urban environmental planning.

Number of works: 16661  |  Total number of citations: 17318

Topic detailsв OpenAlex

Advanced Data Processing Techniques

This cluster of papers focuses on the modeling and control of multidimensional systems, with an emphasis on redundant transmission, fuzzy controller adaptation, fault tolerance, real-time systems, and energy efficiency in various domains such as cyber-physical systems, network traffic analysis, and industrial automation.

Number of works: 60256  |  Total number of citations: 206829

Topic detailsв OpenAlex

Advanced Computational Techniques in Science and Engineering

This cluster of papers focuses on the intersection of Internet of Things (IoT) and healthcare systems, including topics such as remote monitoring, algorithmic modeling, wireless sensor networks, telemedicine, biomedical signal processing, and digital information management. The papers also touch upon the application of IoT in smart city healthcare systems and the use of corpus analysis in technical writing classrooms.

Number of works: 19217  |  Total number of citations: 82460

Topic detailsв OpenAlex

Work details in OpenAlex

Article type: scientific article

DOI: https://doi.org/10.17759/mda.2020100306

Published

For citation: Ardabyevskiy, P.A., Gonchar, D.A., Kan, Y.S. (2020). Statistical Simulation of the Probability Distribution Kernel and Its Application to Solve the Quantile Optimization Problem with the Bilinear Loss Function. Modelling and Data Analysis, 10(3), 69–84. (In Russ.). https://doi.org/10.17759/mda.2020100306

© Ardabyevskiy P.A., Gonchar D.A., Kan Y.S., 2020

License: CC BY-NC 4.0

References

  1. Kibzun A.I., Kan Y.S. Zadachi stohasticheskogo programmirovaniya s veroyatnostnymi kriteriyami. – M.: Fizmatlit, 2009.
  2. Kan Y.S. Formirovanie portfelej cennyh bumag s uchetom riska. M.: MAI publishing, 2008.
  3. Kan Y.S., Tuzov N.V. Minimizaciya kvantili normal’nogo raspredeleniya bilinejnoj funkcii poter’. Avtomatika i Telemekhanika. 1998, № 11, pp. 82–92.
  4. Vasil’eva S.N., Kan Y.S. Metod resheniya zadachi kvantil’noj optimizacii s bilinejnoj funkciej poter’ . Avtomatika i Telemekhanika, 2015, № 9, pp/ 83–101.
  5. Kan Y.S. Rasshirenie zadachi kvantil’noj optimizacii s linejnoj po sluchajnym parametram funkciej poter’ . Avtomatika i Telemekhanika, 2020, № 12.
  6. Vasil’eva S.N., Kan Y.S. Algoritm vizualizacii ploskogo yadra veroyatnostnoj mery. Informatika i ee primeneniya, 2018, № 2, pp. 60–68.

Information About the Authors

Pavel A. Ardabyevskiy, Student of the magistracy, Moscow Aviation Institute (National Research University), Moscow, Russian Federation, ORCID: https://orcid.org/0000-0002-6857-7485, e-mail: ardpavel@gmail.com

Dmitry A. Gonchar, Student of the Magistracy, Moscow Aviation Institute (National Research University), Moscow, Russian Federation, ORCID: https://orcid.org/0000-0002-2414-491X, e-mail: dima.gonchar.29.08.13@gmail.com

Yuri S. Kan, Doctor of Physics and Matematics, Professor, Moscow Aviation Institute (National Research University), Moscow, Russian Federation, ORCID: https://orcid.org/0000-0001-9950-4716, e-mail: yu_kan@mail.ru

Metrics

 Web Views

Whole time: 437
Previous month: 9
Current month: 10

 PDF Downloads

Whole time: 150
Previous month: 5
Current month: 7

 Total

Whole time: 587
Previous month: 14
Current month: 17