Lancaster EPrints

Clustering as a tool for self-generation of intelligent systems : a survey.

Dutta Baruah, Rashmi and Angelov, Plamen (2010) Clustering as a tool for self-generation of intelligent systems : a survey. In: Evolving Intelligent Systems, EIS'10, 2010-03-292010-04-01.

PDF (Rashmi.pdf)
Download (150Kb) | Preview


    Fuzzy Rule Based (FRB) and Neuro-fuzzy systems are commonly used as a basis for intelligent systems due to their transparent and simple human interpretable structure. One of the crucial steps in designing FRB and neuro-fuzzy systems is to innovate the rule base. Data clustering is one of the approaches that have been applied extensively to automatically generate rules from input-output data. The goal of this paper is to critically review some of the most commonly used as well as recently developed clustering techniques, emphasizing their use in rule base generation. The paper explores the shift from offline clustering techniques to online and finally to evolving techniques that originated due to the current demand of adaptive systems.

    Item Type: Contribution to Conference (Paper)
    Journal or Publication Title: Evolving Intelligent Systems, EIS'10
    Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
    Departments: Faculty of Science and Technology > School of Computing & Communications
    ID Code: 33823
    Deposited By: Dr. Plamen Angelov
    Deposited On: 19 Jul 2010 08:58
    Refereed?: Yes
    Published?: Published
    Last Modified: 23 Mar 2018 03:38
    Identification Number:

    Actions (login required)

    View Item