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    Wyświetlanie 1-6 z 6
    Tytuł:
    Cycles in Bayesian Networks
    Autorzy:
    Shayakhmetova, Assem
    Litvinenko, Natalya
    Mamyrbayev, Orken
    Wójcik, Waldemar
    Zhamangarin, Dusmat
    Powiązania:
    https://bibliotekanauki.pl/articles/1844619.pdf
    Data publikacji:
    2021
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    Bayesian networks
    directed graphs
    directed cycles
    propagation
    Bayesian evidence
    Opis:
    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.
    Źródło:
    International Journal of Electronics and Telecommunications; 2021, 67, 2; 181-186
    2300-1933
    Pojawia się w:
    International Journal of Electronics and Telecommunications
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Unraveling key drivers for engineer creativity and meaningfulness of work: Bayesian network approach
    Autorzy:
    Wipulanusat, Warit
    Panuwatwanich, Kriengsak
    Stewart, Rodney A.
    Parnphumeesup, Piya
    Sunkpho, Jirapon
    Powiązania:
    https://bibliotekanauki.pl/articles/407381.pdf
    Data publikacji:
    2020
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    creativity
    work meaningfulness
    path analysis
    Bayesian networks
    engineers
    Opis:
    This study builds on an existing structural model developed to examine the influence of leadership and organizational culture on innovation and satisfaction of engineers in Australian public sectors (APS). The objective of this study is to increase the understanding of innovation process with a focus on causal relationships among critical factors. To achieve this objective, the study develops an assessment approach to help predict creativity and work meaningfulness of engineers in the APS. Three quantitative analysis methods were sequentially conducted in this study including correlation analysis, path analysis, and Bayesian networks. A correlation analysis was conducted to pinpoint the strong association between key factors studied. Subsequently, path analysis was employed to identify critical pathways which were accordingly used as a structure to develop Bayesian networks. The findings of the study revealed practical strategies for promoting (1) transformational leadership and (2) innovative culture in public sector organizations since these two factors were found to be key drivers for individual creativity and work meaningfulness of their engineers. This integrated approach may be used as a decision support tool for managing the innovation process for engineers in the public sectors.
    Źródło:
    Management and Production Engineering Review; 2020, 11, 2; 26-37
    2080-8208
    2082-1344
    Pojawia się w:
    Management and Production Engineering Review
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Development and application of a decision making tool for fault diagnosis of turbocompressor based on Bayesian network and fault tree
    Autorzy:
    Lakehal, Abdelaziz
    Nahal, Mourad
    Harouz, Riad
    Powiązania:
    https://bibliotekanauki.pl/articles/406808.pdf
    Data publikacji:
    2019
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    plant maintenance
    prioritization
    Bayesian networks
    fault tree
    diagnosis
    turbocompressor
    Opis:
    Fault Tree is one of the traditional and conventional approaches used in fault diagnosis. By identifying combinations of faults in a logical framework it’s possible to define the structure of the fault tree. The same go with Bayesian networks, but the difference of these probabilistic tools is in their ability to reasoning under uncertainty. Some typical constraints to the fault diagnosis have been eliminated by the conversion to a Bayesian network. This paper shows that information processing has become simple and easy through the use of Bayesian networks. The study presented showed that updating knowledge and exploiting new knowledge does not complicate calculations. The contribution is the structural approach of faults diagnosis of turbo compressor qualitatively and quantitatively, the most likely faults are defined in descending order. The approach presented in this paper has been successfully applied to turbo compressor, which represent vital equipment in petrochemical plant.
    Źródło:
    Management and Production Engineering Review; 2019, 10, 2; 16--24
    2080-8208
    2082-1344
    Pojawia się w:
    Management and Production Engineering Review
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Automation of Information Security Risk Assessment
    Autorzy:
    Akhmetov, Berik
    Lakhno, Valerii
    Chubaievskyi, Vitalyi
    Kaminskyi, Serhii
    Adilzhanova, Saltanat
    Ydyryshbayeva, Moldir
    Powiązania:
    https://bibliotekanauki.pl/articles/2124744.pdf
    Data publikacji:
    2022
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    information security
    audit
    Bayesian network
    artificial neural networks
    Opis:
    An information security audit method (ISA) for a distributed computer network (DCN) of an informatization object (OBI) has been developed. Proposed method is based on the ISA procedures automation by using Bayesian networks (BN) and artificial neural networks (ANN) to assess the risks. It was shown that such a combination of BN and ANN makes it possible to quickly determine the actual risks for OBI information security (IS). At the same time, data from sensors of various hardware and software information security means (ISM) in the OBI DCS segments are used as the initial information. It was shown that the automation of ISA procedures based on the use of BN and ANN allows the DCN IS administrator to respond dynamically to threats in a real time manner, to promptly select effective countermeasures to protect the DCS.
    Źródło:
    International Journal of Electronics and Telecommunications; 2022, 68, 3; 549--555
    2300-1933
    Pojawia się w:
    International Journal of Electronics and Telecommunications
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Cluster Based Optimization of Routing in Distributed Sensor Networks Using Bayesian Networks with Tabu Search
    Autorzy:
    Bhajantri, L. B.
    Nalini, N.
    Powiązania:
    https://bibliotekanauki.pl/articles/226310.pdf
    Data publikacji:
    2014
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    Distributed Sensor Networks
    routing
    cluster head
    Bayesian Network
    tabu search
    Opis:
    Distributed Sensor Networks (DSNs) have attracted significant attention over the past few years. A growing list of many applications can employ DSNs for increased effectiveness especially in hostile and remote are as. In all application salargen umber of sensors are expected and requiring careful architecture and management of the net work. Grouping nodes in toclusters has been the most popular approach for support scalability in DSN. This paper proposes acluster based optimization of routing in DSN by employing a Bayesi an network (BN) with Tabu search (TS) approach. BN based approach is used to select efficient cluster head sand construction of BN for the proposed scheme. This approach in corporates energy level of each node, band width and link efficiency. The optimization of routing is considered as a design issue in DSN due to lack of energy consumption, delay and maximum time required for data transmission between source nodes (cluster heads) to sink node. In this work optimization of routing takes place through cluster head nodes by using TS. Simulations have been conducted to compare the performance of the proposed approach with LEACH protocol. The objective of the proposed work is to improve the performance of network in terms of energy consumption, through put, packet delivery ratio, and time efficiency of optimization of routing. The results hows that the proposed approach perform better than LEACH protocol that utilizes minimum energy, latency for cluster formation and reduce over head of the protocol.
    Źródło:
    International Journal of Electronics and Telecommunications; 2014, 60, 2; 199-208
    2300-1933
    Pojawia się w:
    International Journal of Electronics and Telecommunications
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Optimisation of neural state variables estimators of two-mass drive system using the Bayesian regularization method
    Autorzy:
    Kamiński, M.
    Orłowska-Kowalska, T.
    Powiązania:
    https://bibliotekanauki.pl/articles/202379.pdf
    Data publikacji:
    2011
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    electrical drive
    two-mass system
    state estimation
    neural networks
    training methods
    Bayesian regularization
    Opis:
    The paper deals with the application of neural networks for state variables estimation of the electrical drive system with an elastic joint. The torsional vibration suppression of such drive system is achieved by the application of a special control structure with a state-space controller and additional feedbacks from mechanical state variables. Signals of the torsional torque and the load-machine speed, estimated by neural networks are used in the control structure. In the learning procedure of the neural networks a modified objective function with the regularization technique is introduced. For choosing the regularization parameters, the Bayesian interpretation of neural networks is used. It gives a possibility to calculate automatically these parameters in the learning process. In this work results obtained with the classical Levenberg-Marquardt algorithm and the expanded one by a regularization function are compared. High accuracy of the reconstructed signals is obtained without the necessity of the electrical drive system parameters identification. Simulation results show good precision of both presented neural estimators for a wide range of changes of the load speed and torque. Simulation results are verified by the laboratory experiments.
    Źródło:
    Bulletin of the Polish Academy of Sciences. Technical Sciences; 2011, 59, 1; 33-38
    0239-7528
    Pojawia się w:
    Bulletin of the Polish Academy of Sciences. Technical Sciences
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-6 z 6

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