Fuzzy Logic Model for Predicting the Number of Online Courses Needed from Number of Students Enrolled in Higher Education
نویسندگان
چکیده
Context: In Higher Education where online courses are offered, one need is to predict the number of courses to be open. At date, some types of models have been used for this goal, such as models based upon machine learning, statistical and softcomputing approaches. Goal: To propose a softcomputing model for predicting the number of online courses (NOC) needed from the number of students enrolled in Higher Education. Hypothesis: Prediction accuracy of a fuzzy model is better or equal than a statistical regression model. Results: Prediction accuracy of a fuzzy model was slightly better than that of a statistical regression model Conclusion: Fuzzy logic could be applied for predicting the NOC needed from the number of students enrolled in Higher Education.
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