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Please use this identifier to cite or link to this item: http://hdl.handle.net/10525/786

Title: New Knowledge Obtaining in Structural-predicate Models of Knowledge
Authors: Koval, Valeriy
Kuk, Yuriy
Keywords: New Knowledge
Predicates
Complex Objects
Primary Objects
Maximal Discernibleness
Issue Date: 2005
Publisher: Institute of Information Theories and Applications FOI ITHEA
Abstract: An effective mathematical method of new knowledge obtaining on the structure of complex objects with required properties is developed. The method comprehensively takes into account information on the properties and relations of primary objects, composing the complex objects. It is based on measurement of distances between the predicate groups with some interpretation of them. The optimal measure for measurement of these distances with the maximal discernibleness of different groups of predicates is constructed. The method is tested on solution of the problem of obtaining of new compound with electro-optical properties.
URI: http://hdl.handle.net/10525/786
ISSN: 1313-0463
Appears in Collections:Volume 12 Number 1

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