IDEAS home Printed from https://ideas.repec.org/a/wsi/ijmpcx/v34y2023i01ns012918312350002x.html
   My bibliography  Save this article

An adaptive scaling technique to quantum clustering

Author

Listed:
  • Mehdi Nabatian

    (Department of Physics, Azarbaijan Shahid Madani University, 35 Km Tabriz-Maragheh Road, Tabriz 009851, East Azerbaijan, Iran)

  • Jafar Tanha

    (��Department of Computer Engineering, Faculty of Electrical and Computer Engineering, Tabriz University, 29 Bahman Blvd, Tabriz 009851, East Azerbaijan, Iran)

  • Alireza Rastkar Ebrahimzadeh

    (Department of Physics, Azarbaijan Shahid Madani University, 35 Km Tabriz-Maragheh Road, Tabriz 009851, East Azerbaijan, Iran)

  • Arash Phirouznia

    (Department of Physics, Azarbaijan Shahid Madani University, 35 Km Tabriz-Maragheh Road, Tabriz 009851, East Azerbaijan, Iran)

Abstract

Data clustering is an essential tool for entering the data world. Quantum clustering (QC) is a meta-heuristic method derived from the Schrödinger equation and incorporates some concepts of quantum mechanics. QC shows a very high ability to adapt to data distribution and finding data structure. The data are clustered by the extremes of the potential function obtained from the Schrödinger equation. QC has a length parameter that plays an important task in determining the number and location of extremes of the potential function. The length parameter is the width of the Gaussian kernel that is included as a wave function in the Schrödinger equation. In this paper, we use a simple method to estimate the width of the Gaussian kernel based on an adaptive scaling technique. In adaptive scaling quantum clustering (ASQC), global hyper-parameter of QC is replaced by a local hyper-parameter. By this technique, the effects of local density are entered in QC, the necessary parameters for this model are calculated by algorithm and the clustering results are improved.

Suggested Citation

  • Mehdi Nabatian & Jafar Tanha & Alireza Rastkar Ebrahimzadeh & Arash Phirouznia, 2023. "An adaptive scaling technique to quantum clustering," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 34(01), pages 1-17, January.
    • Handle: RePEc:wsi:ijmpcx:v:34:y:2023:i:01:n:s012918312350002x
    DOI: 10.1142/S012918312350002X
    as

    Download full text from publisher

    File URL: http://www.worldscientific.com/doi/abs/10.1142/S012918312350002X
    Download Restriction: Access to full text is restricted to subscribers
    File URL: https://libkey.io/10.1142/S012918312350002X?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jasim, Ali Kadhim & Tanha, Jafar & Balafar, Mohammad Ali, 2024. "Neighborhood information based semi-supervised fuzzy C-means employing feature-weight and cluster-weight learning," Chaos, Solitons & Fractals, Elsevier, vol. 181(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:wsi:ijmpcx:v:34:y:2023:i:01:n:s012918312350002x. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Tai Tone Lim (email available below). General contact details of provider: http://www.worldscinet.com/ijmpc/ijmpc.shtml .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.