Sie können Bookmarks mittels Listen verwalten, loggen Sie sich dafür bitte in Ihr SLUB Benutzerkonto ein.
Medientyp:
E-Artikel
Titel:
A Novel Technique for Solving Fully Fuzzy Nonlinear Systems Based on Neural Networks
Beteiligte:
Jafari, Raheleh;
Razvarz, Sina;
Gegov, Alexander
Erschienen:
World Scientific Pub Co Pte Lt, 2020
Erschienen in:Vietnam Journal of Computer Science
Sprache:
Englisch
DOI:
10.1142/s2196888820500050
ISSN:
2196-8888;
2196-8896
Entstehung:
Anmerkungen:
Beschreibung:
<jats:p> Predicting the solutions of complex systems is a crucial challenge. Complexity exists because of the uncertainty as well as nonlinearity. The nonlinearity in complex systems makes uncertainty irreducible in several cases. In this paper, two new approaches based on neural networks are proposed in order to find the estimated solutions of the fully fuzzy nonlinear system (FFNS). For obtaining the estimated solutions, a gradient descent algorithm is proposed in order to train the proposed networks. An example is proposed in order to show the efficiency of the considered approaches. </jats:p>