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Algebraic Bayesian Networks: Local Probabilistic-Logic Inference Machine Architecture and Set of Minimal Joint Graphs. / Mal’chevskaya, E. A.; Berezin, A. I.; Zolotin, A. A.; Tulupyev, A. L.

Proceedings of the First International Scientific Conference «Intelligent Information Technologies for Industry» (IITI'16). Springer Nature, 2016. стр. 69-79.

Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференций › статья в сборнике › научная

Harvard

Mal’chevskaya, EA, Berezin, AI, Zolotin, AA & Tulupyev, AL 2016, Algebraic Bayesian Networks: Local Probabilistic-Logic Inference Machine Architecture and Set of Minimal Joint Graphs. в Proceedings of the First International Scientific Conference «Intelligent Information Technologies for Industry» (IITI'16). Springer Nature, стр. 69-79.

APA

Mal’chevskaya, E. A., Berezin, A. I., Zolotin, A. A., & Tulupyev, A. L. (2016). Algebraic Bayesian Networks: Local Probabilistic-Logic Inference Machine Architecture and Set of Minimal Joint Graphs. в Proceedings of the First International Scientific Conference «Intelligent Information Technologies for Industry» (IITI'16) (стр. 69-79). Springer Nature.

Vancouver

Mal’chevskaya EA, Berezin AI, Zolotin AA, Tulupyev AL. Algebraic Bayesian Networks: Local Probabilistic-Logic Inference Machine Architecture and Set of Minimal Joint Graphs. в Proceedings of the First International Scientific Conference «Intelligent Information Technologies for Industry» (IITI'16). Springer Nature. 2016. стр. 69-79

Author

Mal’chevskaya, E. A. ; Berezin, A. I. ; Zolotin, A. A. ; Tulupyev, A. L. / Algebraic Bayesian Networks: Local Probabilistic-Logic Inference Machine Architecture and Set of Minimal Joint Graphs. Proceedings of the First International Scientific Conference «Intelligent Information Technologies for Industry» (IITI'16). Springer Nature, 2016. стр. 69-79

BibTeX

@inbook{ce1a1e03701444aab481dd5ec2675028,
title = "Algebraic Bayesian Networks: Local Probabilistic-Logic Inference Machine Architecture and Set of Minimal Joint Graphs",
abstract = "The paper considers a C# software package that implements algorithms of the local probabilistic-logical inference in algebraic Bayesian networks and the synthesis of their secondary structure. The package supports local network con- sistency verification and maintenance, priori and posteriori inference operations. In addition, two assembly algorithms for generating the set of minimal joint graphs and a usage example for one of them are presented. These algorithms provide algebraic Bayesian networks visualisation and are intended for structured entry data representation in GUI as well as for global evidence propagation and other probabilistic-logic inference operations implementation based on their local homologues.",
keywords = "Algebraic Bayesian networks, Probabilistic-logic inference, Secondary structure synthesis, Assembly algorithms, Minimal joint graph",
author = "Mal{\textquoteright}chevskaya, {E. A.} and Berezin, {A. I.} and Zolotin, {A. A.} and Tulupyev, {A. L.}",
year = "2016",
language = "English",
isbn = "978-3-319-33609-1",
pages = "69--79",
booktitle = "Proceedings of the First International Scientific Conference «Intelligent Information Technologies for Industry» (IITI'16)",
publisher = "Springer Nature",
address = "Germany",

}

RIS

TY - CHAP

T1 - Algebraic Bayesian Networks: Local Probabilistic-Logic Inference Machine Architecture and Set of Minimal Joint Graphs

AU - Mal’chevskaya, E. A.

AU - Berezin, A. I.

AU - Zolotin, A. A.

AU - Tulupyev, A. L.

PY - 2016

Y1 - 2016

N2 - The paper considers a C# software package that implements algorithms of the local probabilistic-logical inference in algebraic Bayesian networks and the synthesis of their secondary structure. The package supports local network con- sistency verification and maintenance, priori and posteriori inference operations. In addition, two assembly algorithms for generating the set of minimal joint graphs and a usage example for one of them are presented. These algorithms provide algebraic Bayesian networks visualisation and are intended for structured entry data representation in GUI as well as for global evidence propagation and other probabilistic-logic inference operations implementation based on their local homologues.

AB - The paper considers a C# software package that implements algorithms of the local probabilistic-logical inference in algebraic Bayesian networks and the synthesis of their secondary structure. The package supports local network con- sistency verification and maintenance, priori and posteriori inference operations. In addition, two assembly algorithms for generating the set of minimal joint graphs and a usage example for one of them are presented. These algorithms provide algebraic Bayesian networks visualisation and are intended for structured entry data representation in GUI as well as for global evidence propagation and other probabilistic-logic inference operations implementation based on their local homologues.

KW - Algebraic Bayesian networks

KW - Probabilistic-logic inference

KW - Secondary structure synthesis

KW - Assembly algorithms

KW - Minimal joint graph

M3 - Article in an anthology

SN - 978-3-319-33609-1

SP - 69

EP - 79

BT - Proceedings of the First International Scientific Conference «Intelligent Information Technologies for Industry» (IITI'16)

PB - Springer Nature

ER -

ID: 7566524