Detail publikačního výsledku

Using AI Methods to Find a Non-Linear Regression Model with a Coupling Condition

MATOUŠEK, R.

Originální název

Using AI Methods to Find a Non-Linear Regression Model with a Coupling Condition

Anglický název

Using AI Methods to Find a Non-Linear Regression Model with a Coupling Condition

Druh

Článek recenzovaný mimo WoS a Scopus

Originální abstrakt

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).

Anglický abstrakt

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).

Klíčová slova

Regression, RBF, Neural netvork, Genetic algorithm

Klíčová slova v angličtině

Regression, RBF, Neural netvork, Genetic algorithm

Autoři

MATOUŠEK, R.

Rok RIV

2012

Vydáno

05.01.2011

Nakladatel

Pavel Heriban

Místo

Brno

ISSN

1802-1484

Periodikum

Engineering Mechanics

Svazek

17

Číslo

5/6

Stát

Česká republika

Strany od

419

Strany do

431

Strany počet

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",
  pages="419--431",
  issn="1802-1484"
}