مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Persian Verion

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

video

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

sound

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Persian Version

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

View:

1,545
مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Download:

0
مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Cites:

Information Journal Paper

Title

AN ARTIFICIAL NEURAL NETWORK MODEL TO PREDICT THE SERVICE QUALITY OF ACADEMIC LIBRARIES

Pages

  24-33

Keywords

NEURAL NETWORKS (COMPUTER)Q2

Abstract

 Introduction: Commonly libraries and information centers use LibQual to measure their quality of services. Although analysis of Libqual done with classical statistics, it is possible to analyze it through Artificial Neural Network with lower error rate. This research try to introduce an Artificial Neural Network that is able to predict service quality of university library.Methods: In this applied cross-sectional study, all of Shiraz university of medical science students were assessed. LibQual questionnaire was the instrument of data collection and MATLAB software was being used to analyze data. In addition an algorithm was written to automatic selection of the best network architecture based on lower error rate and higher adaptation rate.Results: for 5 categories of input data and with running of the written algorithm, 5 ANN was created and their matching ratio is 0.77059, 0.6828, 0.81089, 0.79161 and 0.83273 respectively.Conclusion: By comparing the ANNs, it was found that ANN with 20 hidden layer, %80 training data, %16.667 testing data and %3.3333 validation data that be fed with fifth input data, is the most appropriate ANN in quality evaluation of university libraries.

Cites

  • No record.
  • References

  • No record.
  • Cite

    APA: Copy

    MOHEBBI, Z., SEDGHI, S., ROUDBARI, M., & GHOLAMNEJAD, J.. (2013). AN ARTIFICIAL NEURAL NETWORK MODEL TO PREDICT THE SERVICE QUALITY OF ACADEMIC LIBRARIES. JOURNAL OF HEALTH ADMINISTRATION, 16(54), 24-33. SID. https://sid.ir/paper/130134/en

    Vancouver: Copy

    MOHEBBI Z., SEDGHI S., ROUDBARI M., GHOLAMNEJAD J.. AN ARTIFICIAL NEURAL NETWORK MODEL TO PREDICT THE SERVICE QUALITY OF ACADEMIC LIBRARIES. JOURNAL OF HEALTH ADMINISTRATION[Internet]. 2013;16(54):24-33. Available from: https://sid.ir/paper/130134/en

    IEEE: Copy

    Z. MOHEBBI, S. SEDGHI, M. ROUDBARI, and J. GHOLAMNEJAD, “AN ARTIFICIAL NEURAL NETWORK MODEL TO PREDICT THE SERVICE QUALITY OF ACADEMIC LIBRARIES,” JOURNAL OF HEALTH ADMINISTRATION, vol. 16, no. 54, pp. 24–33, 2013, [Online]. Available: https://sid.ir/paper/130134/en

    Related Journal Papers

    Related Seminar Papers

  • No record.
  • Related Plans

  • No record.
  • Recommended Workshops






    Move to top
    telegram sharing button
    whatsapp sharing button
    linkedin sharing button
    twitter sharing button
    email sharing button
    email sharing button
    email sharing button
    sharethis sharing button