Analysis of a rule-based curriculum plan optimization system with Spearman rank correlation
Küçük Resim Yok
Tarih
2014
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Tubitak Scientific & Technical Research Council Turkey
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
In corporations, accurate planning should be applied to manage the in-service training task within an optimum time period and without hindering the working tempo of the employees. For this reason, it is better to consider the curriculum planning task as a timetabling problem. However, when the timetables are prepared manually, it may turn out to be a complicated and time-consuming problem. In this study, it is aimed to evaluate the results of software introduced previously, which seeks to find a solution to the curriculum planning problem of in-service training programs in corporations using a rule-based genetic algorithm (GA). The input data of the GA is the prerequisite rule set of the modules of the training program, where these rules are used for the fitness function of the system. The results are compared with the suggestion of an expert trainer using a nonparametric correlation test, and the best parameter combination of the GA giving the most similar result to that of the expert's is determined. According to the tests, the results gathered are considered to be 97% reliable when compared with the suggested module range.
Açıklama
Anahtar Kelimeler
Genetic algorithm, rule base, curriculum plan optimization, Spearman rank correlation
Kaynak
Turkish Journal of Electrical Engineering and Computer Sciences
WoS Q Değeri
Q4
Scopus Q Değeri
Q3
Cilt
22
Sayı
1
