InterCriteria Analysis results based on different number of objects
Dafina Zoteva, Olympia Nikolaeva Roeva · Notes on Intuitionistic Fuzzy Sets · 2018
InterCriteria Analysis (ICrA) results based on different number of objects are investigated in this paper.To evaluate the influence of the number of objects, data from parameter identification procedures of an E. coli fed-batch fermentation process model are used.Model parameters are estimated applying 100 genetic algorithms with different mutation rate values.Seven different index matrices are constructed for ICrA.The results show that the number of objects in ICrA is important for the reliability of the obtained results.