Work

Cycles in Bayesian Networks

Year: 2021

Type: article

Abstract: The article is devoted to some critical problems of using Bayesian networks for solving practical problems, in which graph models contain directed cycles. The strict requirement of the acyclicity of the directed graph representing the Bayesian network does not allow to efficiently solve most of the problems that contain directed cycles. The modern theory of Bayesian networks prohibits the use of directed cycles. The requirement of acyclicity of the graph can significantly simplify the general theory of Bayesian networks, significantly simplify the development of algorithms and their implementation in program code for calculations in Bayesian networks..

Source: International Journal of Electronics and Telecommunications

DOI: 10.24425/ijet.2021.135962

Authors: Assem Shayakhmetova, Natalya Litvinenko, Orken Mamyrbayev, Waldemar Wójcik, Dusmat Zhamangarin

Institutions: Al-Farabi Kazakh National University, Institute of Information and Computational Technologies, Kazakh University Ways of Communications, Lublin University of Technology

Language: English

Topic: Bayesian Modeling and Causal Inference

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $115

OpenAlex ID: W3161123260