Please use this identifier to cite or link to this item: http://er.nau.edu.ua:8080/handle/NAU/31694
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dc.contributor.authorS.Dmitriev-
dc.contributor.authorO.Popov-
dc.contributor.authorO.Yakushenko-
dc.contributor.authorV.Potapov-
dc.contributor.authoro.Pashchuk-
dc.date.accessioned2017-12-06T09:53:43Z-
dc.date.available2017-12-06T09:53:43Z-
dc.date.issued2017-09-
dc.identifier.urihttp://er.nau.edu.ua:8080/handle/NAU/31694-
dc.description.abstractThe paper is dedicated to the relevant problem that pertains to gas turbine engines diagnosing. The issue con- sidered in the paper is how to diagnose gas turbine engines using the methods of pattern recognition: in par- ticular the method of “binary tree” and the “nearest neighbor” method. In computer science, a binary tree is a tree data structure in which each node has at most two children, which are referred to as the left child and the right child. A recursive definition using just set theory notions is that a (non-empty) binary tree is a triple (L, S, R), where L and R are binary trees or the empty set and S is a singleton set. Some authors allow the binary tree to be the empty set as well. I n computing, binary trees are seldom used solely for their struc- ture. Much more typical is to define a labeling function on the nodes, which associates some value to each node. Nearest neighbor search (NNS), as a form of proximity search, is the optimization problem of finding the point in a given set that is closest (or most similar) to a given point. Closeness is typically expressed in terms of a dissimilarity function: the less similar thuk_UA
dc.language.isoen_USuk_UA
dc.publisherАвиационно–космическая техника и технология.–Харківuk_UA
dc.relation.ispartofseries;№ 8 (143)-
dc.subjectdiagnosing, gas turbine engines, binary tree, pattern recognition, nearest neighbor, classification, measure of distanceuk_UA
dc.titleGas turbine engines diagnosing using the methods of pattern recognitionuk_UA
dc.typeArticleuk_UA
Appears in Collections:Наукові статті кафедри авіаційних двигунів

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