2013-2014 > Academic research: refereed > Publication in refereed journalAccepted ManuscriptRGCPolyU5134/12EPublishe
This paper proposes a fast learning method for fuzzy measure determination named fuzzy extreme learn...
In this paper, a new way of optimizing fuzzy logic is introduced. This way is used to optimize the o...
This paper presents a fuzzy extreme learning machine (F-ELM) that embeds fuzzy membership functions ...
A challenge in modeling type-2 fuzzy logic systems is the development of efficient learning algorith...
In this paper, a hybrid training model for interval type-2 fuzzy logic system is proposed. The hybri...
Extreme learning machine (ELM) is originally proposed for single- hidden layer feed-forward neural n...
Abstract:- This article presents a new learning methodology based on a hybrid algorithm for interval...
Research reported here proves that Interval Type-2 Fuzzy Systems can be carried out using type-1 fuz...
This paper describes a self-evolving interval type-2 fuzzy neural network (FNN) for various applicat...
This paper investigates the feasibility of applying a relatively novel neural network technique, i.e...
Evolutionary Extreme Learning Machine (E-ELM) is frequently much more efficient than traditional gra...
10.1016/j.engappai.2005.12.011Engineering Applications of Artificial Intelligence198829-841EAAI
Abstract—For many classification or controlling problems a set of training data is available. To mak...
Fuzzy Classifier (GT2FC) for online rule learning from real-time data streams. While in batch rule l...
This book reviews current state of the art methods for building intelligent systems using type-2 fuz...
This paper proposes a fast learning method for fuzzy measure determination named fuzzy extreme learn...
In this paper, a new way of optimizing fuzzy logic is introduced. This way is used to optimize the o...
This paper presents a fuzzy extreme learning machine (F-ELM) that embeds fuzzy membership functions ...
A challenge in modeling type-2 fuzzy logic systems is the development of efficient learning algorith...
In this paper, a hybrid training model for interval type-2 fuzzy logic system is proposed. The hybri...
Extreme learning machine (ELM) is originally proposed for single- hidden layer feed-forward neural n...
Abstract:- This article presents a new learning methodology based on a hybrid algorithm for interval...
Research reported here proves that Interval Type-2 Fuzzy Systems can be carried out using type-1 fuz...
This paper describes a self-evolving interval type-2 fuzzy neural network (FNN) for various applicat...
This paper investigates the feasibility of applying a relatively novel neural network technique, i.e...
Evolutionary Extreme Learning Machine (E-ELM) is frequently much more efficient than traditional gra...
10.1016/j.engappai.2005.12.011Engineering Applications of Artificial Intelligence198829-841EAAI
Abstract—For many classification or controlling problems a set of training data is available. To mak...
Fuzzy Classifier (GT2FC) for online rule learning from real-time data streams. While in batch rule l...
This book reviews current state of the art methods for building intelligent systems using type-2 fuz...
This paper proposes a fast learning method for fuzzy measure determination named fuzzy extreme learn...
In this paper, a new way of optimizing fuzzy logic is introduced. This way is used to optimize the o...
This paper presents a fuzzy extreme learning machine (F-ELM) that embeds fuzzy membership functions ...
DOI
Add to ORKG