Publication detail
Using AI Methods to Find a Non-Linear Regression Model with a Coupling Condition
MATOUŠEK, R.
Czech title
Užití metod umělé inteligence pro nalezení nelineárního regresního modelu s vazební podmínkou
English title
Using AI Methods to Find a Non-Linear Regression Model with a Coupling Condition
Type
journal article - other
Language
en
Original abstract
In the real-life engineering practice, non-linear regression models have to be designed rather often. To ensure their technical or physical feasibility, such models may, in addition, require another coupling condition. This paper describes two procedures for designing a specific non-linear model using AI methods. A Radial Basis Functions (RBF) based optimization is presented of the model using Genetic Algorithms (GA).
Czech abstract
V reálných aplikacích se v otázce regrese často uplatňují podmínky dané fyzikální podstatou (např. neze uvažovat teplotu pod danou mez apod.). V tomto příspěvku je řešen problém návrhu nelineárního regresniho modelu s vazební podmínkou nezápornosti. Příklad je uveden na reálných technologických datech. K řešení je využito RBF neuronové sítě a pokročilého genetického algoritmu.
English abstract
In the real-life engineering practice, non-linear regression models have to be designed rather often. To ensure their technical or physical feasibility, such models may, in addition, require another coupling condition. This paper describes two procedures for designing a specific non-linear model using AI methods. A Radial Basis Functions (RBF) based optimization is presented of the model using Genetic Algorithms (GA).
Keywords in Czech
Regrese, RBF, Neuronová síť, Genetický algoritmus
Keywords in English
Regression, RBF, Neural netvork, Genetic algorithm
RIV year
2011
Released
05.01.2011
Publisher
Pavel Heriban
Location
Brno
ISSN
1802-1484
Journal
Engineering Mechanics
Volume
17
Number
5/6
Pages from–to
419–431
Pages count
13
BIBTEX
@article{BUT50585,
author="Radomil {Matoušek},
title="Using AI Methods to Find a Non-Linear Regression Model with a Coupling Condition",
journal="Engineering Mechanics",
year="2011",
volume="17",
number="5/6",
month="January",
pages="419--431",
publisher="Pavel Heriban",
address="Brno",
issn="1802-1484"
}