Article

Analysis of visualisation requirements for fuzzy systems

Authors:

Ross BrownAuthors Info & Claims

GRAPHITE '03: Proceedings of the 1st international conference on Computer graphics and interactive techniques in Australasia and South East Asia

Pages 181 - ff

https://doi.org/10.1145/604471.604507

Published: 11 February 2003 Publication History

Abstract

This paper provides a comprehensive analysis of the working and requirements of fuzzy systems with the view to devise appropriate visualisation framework and techniques for these systems using a user- and task-oriented approach. We firstly discuss the nature of fuzzy data and the essential components of typical fuzzy systems, then categorise different visualisation requirements from three perspectives: user of fuzzy systems, designer of fuzzy systems and designer of visualisation systems. The visualisation framework also include mechanisms for capturing users' profiles in order to customise the system to their own needs. We then examine how different visualisation techniques can be adapted to satisfy these requirements. Motivations for an architecture of a visualisation system which is based on a multi-agent approach are also presented.

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Cited By

Diamantopoulos TSymeonidis AHarrison RBener ATurhan B(2015)Towards interpretable defect-prone component analysis using genetic fuzzy systemsProceedings of the Fourth International Workshop on Realizing Artificial Intelligence Synergies in Software Engineering10.5555/2820668.2820677(32-38)Online publication date: 16-May-2015
https://dl.acm.org/doi/10.5555/2820668.2820677
Diamantopoulos TSymeonidis A(2015)Towards Interpretable Defect-Prone Component Analysis Using Genetic Fuzzy SystemsProceedings of the 2015 IEEE/ACM 4th International Workshop on Realizing Artificial Intelligence Synergies in Software Engineering10.1109/RAISE.2015.13(32-38)Online publication date: 17-May-2015
https://dl.acm.org/doi/10.1109/RAISE.2015.13
Zolkepli MDong FHirota K(2014) Visualizing Fuzzy Relationship in Bibliographic Big Data Using Hybrid Approach Combining Fuzzy c -Means and Newman-Girvan Algorithm Journal of Advanced Computational Intelligence and Intelligent Informatics10.20965/jaciii.2014.p089618:6(896-907)Online publication date: 20-Nov-2014
https://doi.org/10.20965/jaciii.2014.p0896
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Index Terms

Analysis of visualisation requirements for fuzzy systems
1. Computing methodologies
  1. Computer graphics

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cover image ACM Conferences

GRAPHITE '03: Proceedings of the 1st international conference on Computer graphics and interactive techniques in Australasia and South East Asia

February 2003

307 pages

ISBN:1581135785

DOI:10.1145/604471

Conference Chairs:
Matt Adcock
CSIRO
,
Ian Gwilt
Waikato University
,
Lee Yong Tsui
Nanyang Technological University

Copyright © 2003 ACM.

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SIGGRAPH: ACM Special Interest Group on Computer Graphics and Interactive Techniques

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Published: 11 February 2003

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GRAPHITE03: International Conference on Computer Graphics and Interactive Techniques in Australasia and South East Asia

February 11 - 14, 2003

Melbourne, Australia

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Overall Acceptance Rate 124 of 241 submissions, 51%

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Cited By

Diamantopoulos TSymeonidis AHarrison RBener ATurhan B(2015)Towards interpretable defect-prone component analysis using genetic fuzzy systemsProceedings of the Fourth International Workshop on Realizing Artificial Intelligence Synergies in Software Engineering10.5555/2820668.2820677(32-38)Online publication date: 16-May-2015
https://dl.acm.org/doi/10.5555/2820668.2820677
Diamantopoulos TSymeonidis A(2015)Towards Interpretable Defect-Prone Component Analysis Using Genetic Fuzzy SystemsProceedings of the 2015 IEEE/ACM 4th International Workshop on Realizing Artificial Intelligence Synergies in Software Engineering10.1109/RAISE.2015.13(32-38)Online publication date: 17-May-2015
https://dl.acm.org/doi/10.1109/RAISE.2015.13
Zolkepli MDong FHirota K(2014) Visualizing Fuzzy Relationship in Bibliographic Big Data Using Hybrid Approach Combining Fuzzy c -Means and Newman-Girvan Algorithm Journal of Advanced Computational Intelligence and Intelligent Informatics10.20965/jaciii.2014.p089618:6(896-907)Online publication date: 20-Nov-2014
https://doi.org/10.20965/jaciii.2014.p0896
Alonso JPancho DCordón OQuirin AMagdalena L(2013)Social Network Analysis of Co-fired Fuzzy RulesSoft Computing: State of the Art Theory and Novel Applications10.1007/978-3-642-34922-5_9(113-128)Online publication date: 2013
https://doi.org/10.1007/978-3-642-34922-5_9
Conti GWatson PShape NDe Amicis RPrandi FLiao L(2011)Enabling the "Internet of Places"Proceedings of the 2nd International Conference on Computing for Geospatial Research & Applications10.1145/1999320.1999329(1-8)Online publication date: 23-May-2011
https://dl.acm.org/doi/10.1145/1999320.1999329
Gelernter JCao DLu RFink ECarbonell J(2009)Creating and visualizing fuzzy document classificationProceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics10.5555/1732323.1732438(672-679)Online publication date: 11-Oct-2009
https://dl.acm.org/doi/10.5555/1732323.1732438
Pham BStreit ABrown R(2008)Visualisation of Information Uncertainty: Progress and Challenges.Trends in Interactive Visualization10.1007/978-1-84800-269-2_2(19-48)Online publication date: 1-Oct-2008
https://doi.org/10.1007/978-1-84800-269-2_2
Yates RWesson J(2006)re-ViewProceedings of the 2006 annual research conference of the South African institute of computer scientists and information technologists on IT research in developing countries10.1145/1216262.1216267(41-50)Online publication date: 9-Oct-2006
https://dl.acm.org/doi/10.1145/1216262.1216267
Pham BBrown R(2005)Visualisation of fuzzy systemsFuture Generation Computer Systems10.5555/1088377.170828121:7(1199-1212)Online publication date: 1-Jul-2005
https://dl.acm.org/doi/10.5555/1088377.1708281
Pham BBrown R(2005)Visualisation of fuzzy systems: requirements, techniques and frameworkFuture Generation Computer Systems10.1016/j.future.2004.04.00721:7(1199-1212)Online publication date: Jul-2005
https://doi.org/10.1016/j.future.2004.04.007
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