Diagnosis of hypoglycemic episodes using a neural network based rule discovery system

KY Chan, SH Ling, TS Dillon, HT Nguyen - Expert Systems with …, 2011 - Elsevier
Hypoglycemia or low blood glucose is dangerous and can result in unconsciousness,
seizures and even death for Type 1 diabetes mellitus (T1DM) patients. Based on the T1DM …

Financial volatility trading using a self-organising neural-fuzzy semantic network and option straddle-based approach

WL Tung, C Quek - Expert Systems with Applications, 2011 - Elsevier
Financial volatility refers to the intensity of the fluctuations in the expected return on an
investment or the pricing of a financial asset due to market uncertainties. Hence, volatility …

eFSM—A novel online neural-fuzzy semantic memory model

WL Tung, C Quek - IEEE Transactions on Neural Networks, 2009 - ieeexplore.ieee.org
Fuzzy rule-based systems (FRBSs) have been successfully applied to many areas.
However, traditional fuzzy systems are often manually crafted, and their rule bases that …

A novel self-organizing fuzzy rule-based system for modelling traffic flow behaviour

C Quek, M Pasquier, B Lim - Expert Systems with applications, 2009 - Elsevier
The study and development of transportation systems have been a focus of attention in
recent years, with many research efforts directed in particular at modelling traffic behaviour …

Natural occurrence of nocturnal hypoglycemia detection using hybrid particle swarm optimized fuzzy reasoning model

SH Ling, HT Nguyen - Artificial Intelligence in Medicine, 2012 - Elsevier
INTRODUCTION: Low blood glucose (hypoglycemia) is a common and serious side effect of
insulin therapy in patients with diabetes. This paper will make a contribution to knowledge in …

A novel brain-inspired neural cognitive approach to SARS thermal image analysis

C Quek, W Irawan, EYK Ng - Expert Systems with Applications, 2010 - Elsevier
Thermal imaging is used extensively in the detection of infrared spectrum. This principle has
found great and effective use in the screening of potential SARS patients. This paper …

RFCMAC: A novel reduced localized neuro-fuzzy system approach to knowledge extraction

RJ Oentaryo, M Pasquier, C Quek - Expert Systems with Applications, 2011 - Elsevier
Neuro-fuzzy system (NFS) and especially localized NFS are powerful rule-based methods
for knowledge extraction, capable of inducing salient knowledge structures from data …

Sohyfis-yager: A self-organizing Yager based hybrid neural fuzzy inference system

SW Tung, C Quek, C Guan - Expert Systems with Applications, 2012 - Elsevier
The Hybrid neural Fuzzy Inference System (HyFIS) is a multilayer adaptive neural fuzzy
system for building and optimizing fuzzy models using neural networks. In this paper, the …

Towards a novel integrated neuro-cognitive architecture (INCA)

RJ Oentaryo, M Pasquier - 2008 IEEE International Joint …, 2008 - ieeexplore.ieee.org
Artificial intelligence research is now flourishing which aims at achieving general, human-
level intelligence. Accordingly, cognitive architectures are increasingly employed as …

T2-hyfis-yager: Type 2 hybrid neural fuzzy inference system realizing yager inference

SW Tung, C Quek, C Guan - 2009 IEEE International …, 2009 - ieeexplore.ieee.org
The hybrid neural fuzzy inference system (Hy-FIS) is a five layers adaptive neural fuzzy
inference system, based on the compositional rule of inference (CRI) scheme, for building …