A Convex Hull-Based Fuzzy Regression to Information Granules Problem – An Efficient Solution to Real-Time Data Analysis

2011 ◽  
pp. 190-204
Author(s):  
Azizul Azhar Ramli ◽  
Junzo Watada ◽  
Witold Pedrycz
Keyword(s):  
Data Analysis ◽  
Convex Hull ◽  
Real Time ◽  
Efficient Solution ◽  
Fuzzy Regression ◽  
Time Data ◽  
Information Granules ◽  
Real Time Data

An Efficient Solution of Real-Time Fuzzy Regression Analysis to Information Granules Problem

2012 ◽  
Vol 16 (2) ◽  
pp. 199-209 ◽  
Author(s):  
Azizul Azhar Ramli ◽  
◽  
Junzo Watada ◽  
Witold Pedrycz ◽  
◽  
...  
Keyword(s):  
Regression Analysis ◽  
Data Analysis ◽  
Convex Hull ◽  
Real Time ◽  
Clustering Algorithm ◽  
System Modeling ◽  
Computing Time ◽  
Fuzzy Regression ◽  
Information Granules ◽  
Hull Structure

Regression models are well known and widely used as one of the important categories of models in system modeling. In this paper, we extend the concept of fuzzy regression in order to handle real-time implementation of data analysis of information granules. An ultimate objective of this study is to develop a hybrid of a genetically-guided clustering algorithm called genetic algorithm-based Fuzzy C-Means (GAFCM) and a convex hull-based regression approach being regarded as a potential solution to the formation of information granules. It is shown that a setting of Granular Computing helps us reduce the computing time, especially in case of real-time data analysis, as well as an overall computational complexity. We propose an efficient real-time information granules regression analysis based on the convex hull approach in which a Beneath-Beyond algorithm is employed to design sub-convex hulls as well as a main convex hull structure. In the proposed design setting, we emphasize a pivotal role of the convex hull approach or more specifically the Beneath-Beyond algorithm, which becomes crucial in alleviating limitations of linear programming manifesting in system modeling.

scholarly journals Real-time data analysis for medical diagnosis using FPGA-accelerated neural networks

2018 ◽  
Vol 19 (S18) ◽  
Author(s):  
Ahmed Sanaullah ◽  
Chen Yang ◽  
Yuri Alexeev ◽  
Kazutomo Yoshii ◽  
Martin C. Herbordt
Keyword(s):  
Neural Networks ◽  
Data Analysis ◽  
Real Time ◽  
Medical Diagnosis ◽  
Time Data ◽  
Real Time Data

scholarly journals Real Time Data Analysis With the ATLAS Trigger at the LHC in Run-2

2020 ◽  
Vol 67 (9) ◽  
pp. 2128-2135
Author(s):  
Pierre-Hugues Beauchemin
Keyword(s):  
Data Analysis ◽  
Real Time ◽  
Time Data ◽  
Real Time Data

Real-time data analysis using a machine learning model significantly improves prediction of successful vaginal deliveries

2020 ◽  
Vol 223 (3) ◽  
pp. 437.e1-437.e15
Author(s):  
Joshua Guedalia ◽  
Michal Lipschuetz ◽  
Michal Novoselsky-Persky ◽  
Sarah M. Cohen ◽  
Amihai Rottenstreich ◽  
...  
Keyword(s):  
Machine Learning ◽  
Data Analysis ◽  
Real Time ◽  
Learning Model ◽  
Time Data ◽  
Machine Learning Model ◽  
Vaginal Deliveries ◽  
Real Time Data
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