Avtor/Urednik		Savšek, Tomaž; Vezjak, Marjan; Pavešić, Nikola
Naslov		Fuzzy tree distance as an effective tool in expert systems
Tip		članek
Vir		In: Ribarić S, editor. Proceedings of the symposium computers in inteligent information systems. Proceedings of the seminar superscalar RISC and CISC processors: Mipro' 96; 1996 May 20-24, Rijeka. Rijeka: Hrvatsko društvo za mikroprocesorske, procesne i informacijske sustave ,
Leto izdaje		1996
Obseg		str. 2-25-30
Jezik		eng
Abstrakt		In the past, reducing complex real-world systems into precise mathematical models was the main tendency in science and engineering. The Operations Research (OR) communced to be applied to real-world decision-making problems. Unfortunately, real-world situations are often not so deterministic. When the knowledge about the system is uncomplete, or when the system is complex and data are episodic rather than systematic, the principles of fuzzy set theory can be applied. On the other hand, graph theory plays an important role in the modeling of structures, especially in system and operational research. The theory of fuzzy graphs has important links to the theory of fuzzy classification and decision analysis. Fuzzy graphs are helpful for representing soft or il-defined structures, for instance, in economy and military systems. With the increasing popularity of using hierarchical data structure and tree construction schemes, which are special class of graphs, we have to face the problem of comparing two tree-like data structures. The problem may arise in many ways: from comparing the tree structure ofan input with that of the templates for classification and decision support or from sorting the data according to the similarity between tree structures for fast retrieval. These situations initiated the study of distance measures for trees. In our paper we would like to present a new approach to the measurement of the distance between fuzzy trees.
Deskriptorji		FUZZY LOGIC EXPERT SYSTEMS DECISION MAKING, COMPUTER-ASSISTED DECISION TREES