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Please use this identifier to cite or link to this item: http://hdl.handle.net/10525/660

Title: Operating Model of Knowledge Quantum Engineering for Decision-Making in Conditions of Indeterminacy
Authors: Molodykh, Liudmyla
Sirodzha, Igor
Keywords: Operating Model
Decision-Making Object
Knowledge Quantum Database
Target Feature
Method of Different-Level Algorithmic Knowledge Quantum
Implicative Law
Issue Date: 2007
Publisher: Institute of Information Theories and Applications FOI ITHEA
Abstract: The operating model of knowledge quantum engineering for identification and prognostic decision- making in conditions of α-indeterminacy is suggested in the article. The synthesized operating model solves three basic tasks: Аt-task to formalize tk-knowledge; Вt-task to recognize (identify) objects according to observed results; Сt-task to extrapolate (prognosticate) the observed results. Operating derivation of identification and prognostic decisions using authentic different-level algorithmic knowledge quantum (using tRAKZ-method) assumes synthesis of authentic knowledge quantum database (BtkZ) using induction operator as a system of implicative laws, and then using deduction operator according to the observed tk-knowledge and BtkZ a derivation of identification or prognostic decisions in a form of new tk-knowledge.
URI: http://hdl.handle.net/10525/660
ISSN: 1313-0463
Appears in Collections:Volume 14 Number 1

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