Monotonic Takagi-Sugeno models with cubic spline membership functions

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F22%3A00354380" target="_blank" >RIV/68407700:21230/22:00354380 - isvavai.cz</a>

Výsledek na webu

<a href="https://doi.org/10.1016/j.eswa.2021.115997" target="_blank" >https://doi.org/10.1016/j.eswa.2021.115997</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.eswa.2021.115997" target="_blank" >10.1016/j.eswa.2021.115997</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Monotonic Takagi-Sugeno models with cubic spline membership functions

Popis výsledku v původním jazyce

In the paper we present sufficient monotonicity conditions for zero order Takagi-Sugeno fuzzy systems with cubic spline membership functions. Those fuzzy models have some advantages comparing with commonly used membership functions. In contrast to triangular membership functions the corresponding mapping is smooth. Comparing to Gaussian membership functions the monotonicity conditions are less conservative, more intuitive and admit membership functions with different width. Finally, the derived monotonicity conditions are formulated as linear constraints on the parameters of fuzzy system that can be easily incorporated into related optimization problems solvable by efficient algorithms. Performance of the proposed fuzzy system is tested on two benchmark datasets and output prediction of a nonlinear dynamical system.

Název v anglickém jazyce

Monotonic Takagi-Sugeno models with cubic spline membership functions

Popis výsledku anglicky

In the paper we present sufficient monotonicity conditions for zero order Takagi-Sugeno fuzzy systems with cubic spline membership functions. Those fuzzy models have some advantages comparing with commonly used membership functions. In contrast to triangular membership functions the corresponding mapping is smooth. Comparing to Gaussian membership functions the monotonicity conditions are less conservative, more intuitive and admit membership functions with different width. Finally, the derived monotonicity conditions are formulated as linear constraints on the parameters of fuzzy system that can be easily incorporated into related optimization problems solvable by efficient algorithms. Performance of the proposed fuzzy system is tested on two benchmark datasets and output prediction of a nonlinear dynamical system.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

20205 - Automation and control systems

Projekt

<a href="/cs/project/GA18-26278S" target="_blank" >GA18-26278S: Zahrnutí apriorní informace při identifikaci nelineárních systémů</a><br>

Návaznosti

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

Rok uplatnění

2022

Kód důvěrnosti údajů

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

Název periodika

Expert Systems with Applications

ISSN

0957-4174

e-ISSN

1873-6793

Svazek periodika

188

Číslo periodika v rámci svazku

February

Stát vydavatele periodika

NL - Nizozemsko

Počet stran výsledku

11

Strana od-do

—

Kód UT WoS článku

000709957800002

EID výsledku v databázi Scopus

2-s2.0-85117413972