USE OF ARTIFICIAL INTELLIGENCE ELEMENTS IN PREDICTIVE PROCESS MANAGEMENT

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F70883521%3A28140%2F22%3A63549321" target="_blank" >RIV/70883521:28140/22:63549321 - isvavai.cz</a>

Result on the web

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DOI - Digital Object Identifier

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Result language

angličtina

Original language name

USE OF ARTIFICIAL INTELLIGENCE ELEMENTS IN PREDICTIVE PROCESS MANAGEMENT

Original language description

Predictive process control is a method of regulation suitable for controlling various types of systems, which is based on the idea of using the prediction of future system behavior and its optimization. Normally, a system model is used to predict behavior, and therefore it is necessary for the correct function of predictive control to make its correct selection and determine its parameters so that the controlled system is described as accurately as possible. Another advantage of predictive control is the possibility of including signal restrictions directly in the controller. The result is the application of some elements of artificial intelligence in suitable areas of predictive control, especially the use of simple evolutionary algorithms in optimization and neural networks as nonlinear models. One of the chapters of the article describes the possibilities of using these elements. It is proved that in addition to classical optimization algorithms, it is also possible to use simple evolutionary algorithms for optimization of prediction, while the computational complexity can be comparable depending on the type of solved problem and settings. The article describes a suitable selection of model systems with slow dynamics, their derivation, and the creation of nonlinear models in the form of scalable neural networks. The potential advantage of this approach for the control of systems that are difficult to describe or for the control of systems whose mathematical-physical description is not known. The chapter of the article also deals with the possibility of using the found models on real systems and determining the necessary conditions and requirements for their application.

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

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OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

<a href="/en/project/EF16_018%2F0002381" target="_blank" >EF16_018/0002381: Development of Research-Oriented Study Programs at FAI</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2022

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

Proceedings of 22nd International Multidisciplinary Scientific GeoConference SGEM 2022, Informatics, Geoinformatics and Remote Sensing

ISBN

978-619-7603-40-8

ISSN

1314-2704

e-ISSN

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Number of pages

9

Pages from-to

1-9

Publisher name

STEF92 Technology Ltd.

Place of publication

Sofia

Event location

Albena

Event date

Jul 4, 2022

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

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