Psychology with soft computing : an integrated approach and its applications

DI NUOVO, Alessandro, CATANIA, V, DI NUOVO, S and BUONO, S (2008). Psychology with soft computing : an integrated approach and its applications. Applied Soft Computing, 8 (1), 829-837.

Full text not available from this repository.
Link to published version:: https://doi.org/10.1016/j.asoc.2007.03.001
Related URLs:

    Abstract

    Soft computing techniques proved to be successful in many application areas. In this paper we investigate the application in psychopathological field of two well known soft computing techniques, fuzzy logic and genetic algorithms (GAs). The investigation started from a practical need: the creation of a tool for a quick and correct classification of mental retardation level, which is needed to choose the right treatment for rehabilitation and to assure a quality of life that is suitable for the specific patient condition. In order to meet this need we researched an adaptive data mining technique that allows us to build interpretable models for automatic and reliable diagnosis. Our work concerned a genetic fuzzy system (GFS), which integrates a classical GA and the fuzzy C-means (FCM) algorithm. This GFS, called genetic fuzzy C-means (GFCM), is able to select the best subset of features to generate an efficient classifier for diagnostic purposes from a database of examples. Additionally, thanks to an extension of the FCM algorithm, the proposed technique could also handle databases with missing values. The results obtained in a practical application on a real database of patients and comparisons with established techniques showed the efficiency of the integrated algorithm, both in data mining and completion.

    Item Type: Article
    Departments - Does NOT include content added after October 2018: Faculty of Science, Technology and Arts > Department of Computing
    Identification Number: https://doi.org/10.1016/j.asoc.2007.03.001
    Page Range: 829-837
    Depositing User: Alessandro Di Nuovo
    Date Deposited: 16 Feb 2016 09:52
    Last Modified: 13 Jun 2017 13:32
    URI: http://shura.shu.ac.uk/id/eprint/11218

    Actions (login required)

    View Item View Item

    Downloads

    Downloads per month over past year

    View more statistics