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    Wyświetlanie 1-4 z 4
    Tytuł:
    Cognitive Modeling and Formation of the Knowledge Base of the Information System for Assessing the Rating of Enterprises
    Autorzy:
    Kryvoruchko, Olena
    Desiatko, Alona
    Karpunin, Igor
    Hnatchenko, Dmytro
    Lakhno, Myroslav
    Malikova, Feruza
    Turdaliev, Ayezhan
    Powiązania:
    https://bibliotekanauki.pl/articles/27311936.pdf
    Data publikacji:
    2023
    Wydawca:
    Polska Akademia Nauk. Czasopisma i Monografie PAN
    Tematy:
    information security
    audit
    Bayesian network
    artificial neural networks
    Opis:
    A mathematical model is proposed that makes it possible to describe in a conceptual and functional aspect the formation and application of a knowledge base (KB) for an intelligent information system (IIS). This IIS is developed to assess the financial condition (FC) of the company. Moreover, for circumstances related to the identification of individual weakly structured factors (signs). The proposed model makes it possible to increase the understanding of the analyzed economic processes related to the company's financial system. An iterative algorithm for IIS has been developed that implements a model of cognitive modeling. The scientific novelty of the proposed approach lies in the fact that, unlike existing solutions, it is possible to adjust the structure of the algorithm depending on the characteristics of a particular company, as well as form the information basis for the process of assessing the company's FC and the parameters of the cognitive model.
    Źródło:
    International Journal of Electronics and Telecommunications; 2023, 69, 4; 697--705
    2300-1933
    Pojawia się w:
    International Journal of Electronics and Telecommunications
    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:
    Grid Fault Diagnosis Based on Information Entropy and Multi-source Information Fusion
    Autorzy:
    Zeng, Xin
    Xiong, Xingzhong
    Luo, Zhongqiang
    Powiązania:
    https://bibliotekanauki.pl/articles/1844639.pdf
    Data publikacji:
    2021
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    information entropy
    Bayesian network
    multi-source information fusion
    D-S evidence theory
    fault diagnosis
    Opis:
    In order to solve the problem of misjudgment caused by the traditional power grid fault diagnosis methods, a new fusion diagnosis method is proposed based on the theory of multi-source information fusion. In this method, the fault degree of the power element is deduced by using the Bayesian network. Then, the time-domain singular spectrum entropy, frequency-domain power spectrum entropy and wavelet packet energy spectrum entropy of the electrical signals of each circuit after the failure are extracted, and these three characteristic quantities are taken as the fault support degree of the power components. Finally, the four fault degrees are normalized and classified as four evidence bodies in the D-S evidence theory for multi-feature fusion, which reduces the uncertainty brought by a single feature body. Simulation results show that the proposed method can obtain more reliable diagnosis results compared with the traditional methods.
    Źródło:
    International Journal of Electronics and Telecommunications; 2021, 67, 2; 143-148
    2300-1933
    Pojawia się w:
    International Journal of Electronics and Telecommunications
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-4 z 4

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