On Equivalence of FIS and ELM for Interpretable Rule-Based Knowledge Representation

This paper presents a fuzzy extreme learning machine (F-ELM) that embeds fuzzy membership functions and rules into the hidden layer of extreme learning machine (ELM). Similar to the concept of ELM that employed the random initialization technique, three parameters of F-ELM are randomly assigned. The...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	IEEE transaction on neural networks and learning systems 2015-07, Vol.26 (7), p.1417-1430
Hauptverfasser:	Wong, Shen Yuong, Yap, Keem Siah, Yap, Hwa Jen, Tan, Shing Chiang, Chang, Siow Wee
Format:	Artikel
Sprache:	eng
Schlagworte:	Accuracy Algorithms Artificial Intelligence Artificial neural networks Benchmarking Classification Computational modeling Databases, Factual Extreme learning machine (ELM) Feedback fuzzy inference system (FIS) Fuzzy Logic Machine Learning Models, Statistical Neural Networks, Computer Neurons pattern classification Power Plants Pragmatics Reproducibility of Results rule based Training
Online-Zugang:	Volltext bestellen
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!