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Journal of Automation and Information Sciences

年間 12 号発行

ISSN 印刷: 1064-2315

ISSN オンライン: 2163-9337

SJR: 0.173 SNIP: 0.588 CiteScore™:: 2

Indexed in

Information-Extreme Algorithm for Optimizing Parameters of Hyperellipsoidal Containers of Recognition Classes

巻 44, 発行 10, 2012, pp. 35-44
DOI: 10.1615/JAutomatInfScien.v44.i10.30
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要約

There has been proposed the algorithm for constructing hyperellipsoidal decision rules during the learning of decision-making system within the frameworks of information-extreme intellectual technology based on maximization of information capacity of the system. The example of algorithm implementation has been shown based on the system to control the manufacturing process of growing scintillate single-crystal from a fusion.

参考
  1. Suykens J.A.K., Horvath G., Basu S., Miechelli C., Vandewalle J. , IOS Press NATO-ASI Series in Computer and Systems Sciences.

  2. Simankov V.S., Lutsenko E.V. , Adaptive control of complex systems based on theory of pattern recognition [in Russian].

  3. Dovbysh A.S. , Foundations of design of intellectual systems: Textbook, [in Ukrainian].

  4. Dovbysh A.S., Martynenko S.S., Kovalenko A.S., Budnyk N.N. , Information-extreme algorithm for recognizing current distribution maps in magnetocardiography.

  5. Dovbysh A.S., Suzdal V.S., Moskalenko S.S. , Intellectual system of decision making support to control a single-crystal growing.

  6. Dovbysh A.S., Chekalov O.P., Martynenko S.S. , Intellectual system of diagnosing oncopathologies, Radio-elektronnyye i kompyuternyye sistemy.

  7. Dovbysh A.S., Vostotskiy V.O. , Information extreme system of decision-making support in cluster analysis mode.

  8. Huber P.J. , Robust statistics [Russian translation].

  9. Vasilenko Yu.A., Vashchuk F.G., Papp I.A. , Approximation of learning sample by hyperparallepiped.

  10. Suzdal V.S., Stadnik P.E., Gerasimchuk L.I., Epifanov Yu.M. , Scintillate single-crystals: automated growing [in Russian].

によって引用された
  1. Dovbysh A. S., Moskalenko V. V., Rizhova A. S., Information-Extreme Method for Classification of Observations with Categorical Attributes, Cybernetics and Systems Analysis, 52, 2, 2016. Crossref

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