Generation of structure function based on ambiguous and incompletely specified data using the fuzzy decision trees

• Published in: 2017 15th International Conference on Emerging eLearning Technologies and Applications (ICETA) pp. 1 - 7
• Main Authors: Rabcan, Jan, Rusnak, Patrik
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.10.2017
• Subjects: Clustering algorithms; Decision trees; Entropy; Mathematical model; Partitioning algorithms; Reliability; System performance
• DOI: 10.1109/ICETA.2017.8102521

The informatics is extremely fast development area that is based on interdisciplinary knowledge. University education for students of this specialisation must include interdisciplinary subjects to illustrate modern trends in researches and technologies. The reliability engineering or reliability analysis is one of typical areas of knowledge that based on principles of interdisciplinary. One of important problem in reliability engineering is development of mathematical model of investigated system. There are a lot methods and algorithms for elaboration of system mathematical model for completely specified information about investigated system. But numerous applied problem must be decided implemented if the initial information is incompletely specified and uncertain. In this case, new methods and algorithms must be developed for the construction of mathematical model. One of possible way for such methods development is based on application of approaches of Data Mining that are focused on the decision of analysis of uncertain and incompletely specified data. New method for mathematical model construction in reliability analysis by Fuzzy Decision Tree is considered in this paper.