Temat: Bayesian neural networks - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: Multi-layered Bayesian Neural Networks for Simulation and Prediction Stress-Strain Time Series
Autorzy:: Krok, A.
Powiązania:: https://bibliotekanauki.pl/articles/308596.pdf
Data publikacji:: 2015
Wydawca:: Instytut Łączności - Państwowy Instytut Badawczy
Tematy:: Bayesian neural networks
Kalman filtering
Opis:: The aim of the paper is to investigate the differences as far as the numerical accuracy is concerned between feedforward layered Artificial Neural Networks (ANN) learned by means of Kalman filtering (KF) and ANN learned by means of the evidence procedure for Bayesian technique. The stress-strain experimental time series for concrete hysteresis loops obtained by the experiment of cyclic loading is presented as considered example.
Źródło:: Journal of Telecommunications and Information Technology; 2015, 3; 45-51
1509-4553
1899-8852
Pojawia się w:: Journal of Telecommunications and Information Technology
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 2.

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

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Skocz do pozycji: 3.

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

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Skocz do pozycji: 4.

Tytuł:: Evolutionary learning of rich neural networks in the Bayesian model selection framework
Autorzy:: Matteucci, M.
Spadoni, D.
Powiązania:: https://bibliotekanauki.pl/articles/907642.pdf
Data publikacji:: 2004
Wydawca:: Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:: sieć neuronowa
model Bayesa
algorytm genetyczny
Rich Neural Networks
Bayesian model selection
genetic algorithm
Bayesian fitness
Opis:: In this paper we focus on the problem of using a genetic algorithm for model selection within a Bayesian framework. We propose to reduce the model selection problem to a search problem solved using evolutionary computation to explore a posterior distribution over the model space. As a case study, we introduce ELeaRNT (Evolutionary Learning of Rich Neural Network Topologies), a genetic algorithm which evolves a particular class of models, namely, Rich Neural Networks (RNN), in order to find an optimal domain-specific non-linear function approximator with a good generalization capability. In order to evolve this kind of neural networks, ELeaRNT uses a Bayesian fitness function. The experimental results prove that ELeaRNT using a Bayesian fitness function finds, in a completely automated way, networks well-matched to the analysed problem, with acceptable complexity.
Źródło:: International Journal of Applied Mathematics and Computer Science; 2004, 14, 3; 423-440
1641-876X
2083-8492
Pojawia się w:: International Journal of Applied Mathematics and Computer Science
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 5.

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

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Skocz do pozycji: 6.

Tytuł:: Konekcjonistyczne modele wyjaśniania procesów poznawczych w kognitywistyce.
Connectionist Models of Explanation of Cognitive Processes in Cognitive Science.
Autorzy:: Pacholik-Żuromska, Anita
Powiązania:: https://bibliotekanauki.pl/articles/521636.pdf
Data publikacji:: 2017
Wydawca:: Uniwersytet Warmińsko-Mazurski w Olsztynie
Tematy:: konekcjonizm
funkcjonalizm
maszyna Turinga
sztuczne sieci neuronowe
Bayesowska teoria indukcji
enaktywizm
connectionism
functionalism
Turing machine
artificial neural networks
Bayesian inference
enactivism
Opis:: Celem artykułu jest przegląd i analiza modeli konekcjonistycznych na tle faz rozwoju kognitywistyki. Konekcjonizm, jako druga faza rozwoju kognitywistyki, zaoferował najlepsze narzędzia wyjaśniania i modelowania procesów poznawczych. Został on przedstawiony w relacji do wcześniejszej i późniejszej fazy rozwoju kognitywistyki. Wykazuje się tu również kompatybilność konekcjonizmu z enaktywizmem (trzecią fazą) na gruncie proponowanego modelu wyjaśniania, jak kształtuje się poznanie.
The aim of this paper is an overview and analysis of the connectionist models on the basis of the milestones in the development of cognitive science. It is claimed that connectionism, as the second phase of cognitive science, offers the best tools of explanation and modelling of cognition. There is also indicated the compatibility of connectionism and enactivism (the third phase) on the basis of the proposed models of explanation.
Źródło:: Humanistyka i Przyrodoznawstwo; 2017, 23; 43-55
1234-4087
Pojawia się w:: Humanistyka i Przyrodoznawstwo
Dostawca treści:: Biblioteka Nauki

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