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Stochastic Optimization Method in Computer Decision Support System

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Advances in Computer Science for Engineering and Education (ICCSEEA 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 754))

Abstract

The questions of parameter optimization are considered in the article. These parameters describe technological processes at ore-dressing plants. There are many problems in creating of automated control systems for such technological processes. Among them are a large number of industrial parameters, the nondeterministic nature of physical and mechanical properties of the raw materials, and many disturbing influences. Thus, to solve these problems authors propose to use an intelligent computer decision support system. It allows calculating a regression equation of some optimization criterion. The complete Kolmogorov-Gabor polynomial is used as a regression model. In addition, the possibility of applying the differential evolution method is analysed. The stochastic optimization method has been compared with the full enumeration method, gradient descent method and Monte Carlo. A simple function with an extremum has been used as an example for demonstrating of search efficiency.

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Authors and Affiliations

  1. Kryvyi Rih National University, 11, Vitaliya Matusevycha str., Kryvyi Rih, 50027, Ukraine

    Andrey Kupin, Ivan Muzyka, Dennis Kuznetsov & Yurii Kumchenko

Authors
  1. Andrey Kupin
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  2. Ivan Muzyka
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  3. Dennis Kuznetsov
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  4. Yurii Kumchenko
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Corresponding author

Correspondence to Ivan Muzyka .

Editor information

Editors and Affiliations

  1. School of Educational Information Technology, Central China Normal University, Wuhan, Hubei, China

    Zhengbing Hu

  2. Mechanical Engineering Research Institute, Russian Academy of Sciences, Moscow, Russia

    Sergey Petoukhov

  3. Faculty of Applied Mathematics, National Technical University of Ukraine “Igor Sikorsky Kiev Polytechnic Institute”, Kiev, Ukraine

    Ivan Dychka

  4. Halmos College of Natural Sciences and Oceanography, Nova Southeastern University, Ft. Lauderdale, Florida, USA

    Matthew He

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Kupin, A., Muzyka, I., Kuznetsov, D., Kumchenko, Y. (2019). Stochastic Optimization Method in Computer Decision Support System. In: Hu, Z., Petoukhov, S., Dychka, I., He, M. (eds) Advances in Computer Science for Engineering and Education. ICCSEEA 2018. Advances in Intelligent Systems and Computing, vol 754. Springer, Cham. https://doi.org/10.1007/978-3-319-91008-6_35

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