Prediction of the Network Administration Course Results Based on Fuzzy Inference

  • Zsolt Csaba Johanyák
  • Szilveszter KovácsEmail author
Part of the Topics in Intelligent Engineering and Informatics book series (TIEI, volume 7)


The prediction of the number of students who will pass or fail the exams in the case of a subject can be very useful information for resource allocation planning purposes. In this chapter, we report on the development of a fuzzy model, that based on the previous performance of currently enrolled students, gives a prediction for the number of students who will fail the exams of the Network Administration course at the end of the autumn semester. These students will usually re-enroll for the course in the spring semester and, conforming to previous experience, will constitute the major part of the enrolling students. The fuzzy model uses a low number of rules and applies a fuzzy rule interpolation based technique (Least Squares based Fuzzy Rule Interpolation) for inference.



This research was supported by the National Scientific Research Fund Grant OKTA K77809. The described work was carried out as part of the TÁMOP-4.2.2/B-10/1-2010-0008 project in the framework of the New Hungarian Development Plan. The realization of this project is supported by the European Union, co-financed by the European Social Fund.


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© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.Kecskemét CollegeDepartment of Information TechnologiesKecskemétHungary
  2. 2.University of MiskolcDepartment of Information TechnologiesMiskolc-EgyetemvárosHungary

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