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Wyświetlanie 1-15 z 54
Tytuł:
Bayesian methods in reliability of search and rescue action
Autorzy:
Burciu, Z.
Powiązania:
https://bibliotekanauki.pl/articles/259315.pdf
Data publikacji:
2010
Wydawca:
Politechnika Gdańska. Wydział Inżynierii Mechanicznej i Okrętownictwa
Tematy:
coordinator
SAR action
reliability
Bayesian network
Opis:
This paper concerns the application of bayesian network to planning and monitoring life saving actions at sea. The presented bayesian network was formed a.o. on the basis of the determined life raft safety function. The proposed bayesian network makes it possible to determine reliability of conducted life saving action, with accounting for a large number of events which influence course of the action. Reliability control was proposed to be applied to search and rescue - SAR action in contrast to risk control. Reliability levels were defined to make the assessing of safety of conducted SAR action, possible.
Źródło:
Polish Maritime Research; 2010, 4; 72-78
1233-2585
Pojawia się w:
Polish Maritime Research
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Wykorzystanie sieci bayesowskich do prognozowania bankructwa firm
Bankruptcy prediction with Bayesian networks
Autorzy:
Gąska, Damian
Powiązania:
https://bibliotekanauki.pl/articles/434020.pdf
Data publikacji:
2016
Wydawca:
Wydawnictwo Uniwersytetu Ekonomicznego we Wrocławiu
Tematy:
bankruptcy prediction
Bayesian network
structure learning
Opis:
The aim of the paper is to compare accuracy of some bankruptcy prediction models based on Bayesian networks. Some network structure learning algorithms were analyzed as a tool for classifiers construction. Empirical analysis was applied to companies listed on Warsaw Stock Exchange. The paper gives short overview of theoretical background behind discussed issues and presents results of empirical analysis.
Źródło:
Śląski Przegląd Statystyczny; 2016, 14 (20); 131-144
1644-6739
Pojawia się w:
Śląski Przegląd Statystyczny
Dostawca treści:
Biblioteka Nauki
Artykuł
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:
Analiza porównawcza wybranych klasyfikatorów w diagnozowaniu uszkodzeń przekładni zębatych
A comparison of selected classifiers in gear fault diagnosis
Autorzy:
Piekoszewski, J.
Powiązania:
https://bibliotekanauki.pl/articles/313178.pdf
Data publikacji:
2017
Wydawca:
Instytut Naukowo-Wydawniczy "SPATIUM"
Tematy:
klasyfikatory
diagnozowanie
sieć bayesowska
classifiers
diagnosis
Bayesian network
Opis:
Niewielkie uszkodzenie przekładni zębatej może prowadzić do poważnej awarii urządzenia. Zatem, bardzo ważnym jest wykrycie takich defektów na ich początkowym etapie powstawania aby zapobiec dalszym uszkodzeniom. Praca przedstawia kilka wybranych teoretycznych narzędzi z obszaru sztucznej inteligencji zastosowanych do rozwiązania problemu diagnozowania uszkodzeń przekładni zębatych. Rozważanymi narzędziami są: perceptron wielowarstwowy, sieć neuronowa o radialnych funkcjach bazowych, drzewo decyzyjne, sieć bayesowska, maszyna wektorów podpierających oraz algorytm k najbliższych sąsiadów. Rezultaty wszystkich eksperymentów zostały otrzymane z wykorzystaniem rzeczywistych danych oraz aplikacji WEKA (ang. Waikato Environment for Knowledge Analysis) dostępnej na stronach Uniwersytetu Waikato w Nowej Zelandii.
Minor gear damage may lead to serious failures of the device. Thus, it is very important to detect such damage as early as possible to prevent further damage. This paper presents a selection of several theoretical tools from the field of artificial intelligence and their application in gear fault classification. The considered tools are: feed forward neural network (multilayer perception), neural network with radial basis functions, decision tree, Bayesian network, support vector machine, and k-nearest neighbor algorithm. All numerical experiments presented in the paper were performed with the use of real-world dataset and WEKA (Waikato Environment for Knowledge Analysis) software, available at the server of the University of Waikato.
Źródło:
Autobusy : technika, eksploatacja, systemy transportowe; 2017, 18, 12; 1233-1236, CD
1509-5878
2450-7725
Pojawia się w:
Autobusy : technika, eksploatacja, systemy transportowe
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:
Bayesian Network Modeling in Discovering Risk Factors of Dental Caries in Three-Year-Old Children
Autorzy:
Łaguna, W.
Bagińska, J.
Oniśko, A.
Powiązania:
https://bibliotekanauki.pl/articles/1918880.pdf
Data publikacji:
2019-08-26
Wydawca:
Uniwersytet Medyczny w Białymstoku
Tematy:
dental caries
Bayesian network
learning from data
risk assessment
Opis:
Purpose - The aim of this study was to use probabilistic graphical models to determine dental caries risk factors in three-year-old children. The analysis was conducted on the basis of the questionnaire data and resulted in building probabilistic graphical models to investigate dependencies among the features gathered in the surveys on dental caries. Materials and Methods - The data available in this analysis came from dental examinations conducted in children and from a questionnaire survey of their parents or guardians. The data represented 255 children aged between 36 and 48 months. Self-administered questionnaires contained 34 questions of socioeconomic and medical nature such as nutritional habits, wealth, or the level of education. The data included also the results of oral examination by a dentist. We applied the Bayesian network modeling to construct a model by learning it from the collected data. The process of Bayesian network model building was assisted by a dental expert. Results - The model allows to identify probabilistic relationships among the variables and to indicate the most significant risk factors of dental caries in three-year-old children. The Bayesian network model analysis illustrates that cleaning teeth and falling asleep with a bottle are the most significant risk factors of dental caries development in three-year-old children, whereas socioeconomic factors have no significant impact on the condition of teeth. Conclusions - Our analysis results suggest that dietary and oral hygiene habits have the most significant impact on the occurrence of dental caries in three-year-olds.
Źródło:
Progress in Health Sciences; 2019, 1; 118-125
2083-1617
Pojawia się w:
Progress in Health Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Reactive energy compensator effect on the reliability of a complex electrical system using Bayesian networks
Autorzy:
Reffas, Omar
Sahraoui, Yacine
Nahal, Mourad
Ghoul, Rachida Hadiby
Saad, Salah
Powiązania:
https://bibliotekanauki.pl/articles/1844423.pdf
Data publikacji:
2020
Wydawca:
Polska Akademia Nauk. Polskie Naukowo-Techniczne Towarzystwo Eksploatacyjne PAN
Tematy:
STATCOM
reliability
Complex Electrical System
reactive energy
Bayesian network
Opis:
The static synchronous compensator is presented in order to improve an electrical network system performance. The present work aims to develop a Bayesian methodology for assessing the time-variant reliability of a complex electrical system taking into account reactive energy compensator (STATCOM). However, the complex aspect is not only related to the complexity of electrical system components architecture, nevertheless is allied to electrical network and STATCOM interactions. The Bayesian network is used for coping with this complexity constraint. The reliability-based assessment of reactive energy compensator effect is applied to a real case of a complex electrical system. The proposed Bayesian methodology application reveals that the STATCOM has a significant influence on electrical system reliability and the developed model can provide valuable information for decision makers to improve the system reliability performance.
Źródło:
Eksploatacja i Niezawodność; 2020, 22, 4; 684-693
1507-2711
Pojawia się w:
Eksploatacja i Niezawodność
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Cross-selling models for telecommunication services
Autorzy:
Jaroszewicz, S.
Powiązania:
https://bibliotekanauki.pl/articles/308093.pdf
Data publikacji:
2008
Wydawca:
Instytut Łączności - Państwowy Instytut Badawczy
Tematy:
cross-selling
telecommunication service
classifier
association rule
Bayesian network
Opis:
Cross-selling is a strategy of selling new products to a customer who has made other purchases earlier. Except for the obvious profit from extra products sold, it also increases the dependence of the customer on the vendor and therefore reduces churn. This is especially important in the area of telecommunications, characterized by high volatility and low customer loyalty. The paper presents two cross-selling approaches: one based on classifiers and another one based on Bayesian networks constructed based on interesting association rules. Effectiveness of the methods is validated on synthetic test data.
Źródło:
Journal of Telecommunications and Information Technology; 2008, 3; 52-59
1509-4553
1899-8852
Pojawia się w:
Journal of Telecommunications and Information Technology
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Forecasting GDP growth rate in Ukraine with alternative models
Autorzy:
Karayuz, I
Bidyuk, P.
Powiązania:
https://bibliotekanauki.pl/articles/118047.pdf
Data publikacji:
2015
Wydawca:
Polskie Towarzystwo Promocji Wiedzy
Tematy:
Regressive model
Bayesian network
short-term forecasting
GDP of Ukraine
Opis:
The problem of constructing mathematical model for short-term fore-casting of GDP is considered. First, extended autoregression is constru-cted that takes two additional independent variables into consideration. The model resulted provides a possibility for generating short-term forecasts of GDP though not of high quality. Another model was constructed in the form of a Bayesian network. The model turned out to be better than the multiple regression, it provides quite good estimates for probabilities of GDP growth direction.
Źródło:
Applied Computer Science; 2015, 11, 3; 88-97
1895-3735
Pojawia się w:
Applied Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Player modeling using Bayesian networks
Modelowanie gracza przy użyciu sieci Bayesowskiej
Autorzy:
Kościuk, K.
Drużdżel, M.
Powiązania:
https://bibliotekanauki.pl/articles/404055.pdf
Data publikacji:
2010
Wydawca:
Polskie Towarzystwo Symulacji Komputerowej
Tematy:
modelowanie gracza
sieć bayesowska
prawdopodobieństwo
player modeling
Bayesian network
probability
Opis:
Typically programs for game playing use the Minimax strategy, which assumes a perfectly rational opponent whose actions are performed optimally. However, most human opponents depart from rationality. In this case, the best move at any given step may not be one that is indicated by MiniMax and an algorithm that takes into consideration humans imperfection will perform better. In order to consider player's weaknesses, it is necessary to model the opponent – learn and know his/her strategies. We build a Bayesian network to model the player. We learn the conditional probability tables in the network from data collected in the course of the game.
Algorytmy grające w gry zazwyczaj używają strategii Minimax zakładającej perfekcyjność przeciwnika, który wybiera zawsze najlepsze ruchy w grze. Gracze jednakże mogą nie działać całkiem racjonalnie. Algorytm, który weźmie to pod uwagę, może dawać lepsze wyniki niż Minimax. Aby wykorzystać słabości przeciwnika, należy stworzyć jego model. W tym celu zbudowaliśmy sieć bayesowską, w której tworzymy tablicę prawdopodobieństw z danych zbieranych w trakcie gry.
Źródło:
Symulacja w Badaniach i Rozwoju; 2010, 1, 2; 151-158
2081-6154
Pojawia się w:
Symulacja w Badaniach i Rozwoju
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Application of the computation procedure in Bayesian network in estimation of total cost of natural stone elements production
Zastosowanie procedury obliczeniowej w sieci Bayesowskiej do wyznaczania kosztów całkowitych produkcji elementów z kamienia naturalnego
Autorzy:
Kusz, A.
Skwarcz, J.
Gryczan, M.
Powiązania:
https://bibliotekanauki.pl/articles/792050.pdf
Data publikacji:
2014
Wydawca:
Komisja Motoryzacji i Energetyki Rolnictwa
Tematy:
production process
natural stone
granite
computation
production cost
Bayesian network
Źródło:
Teka Komisji Motoryzacji i Energetyki Rolnictwa; 2014, 14, 4
1641-7739
Pojawia się w:
Teka Komisji Motoryzacji i Energetyki Rolnictwa
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Maintenance Evaluation and Optimization of a Multi-State System Based on a Dynamic Bayesian Network
Autorzy:
Dahia, Zakaria
Bellaouar, Ahmed
Dron, Jean-Paul
Powiązania:
https://bibliotekanauki.pl/articles/2023959.pdf
Data publikacji:
2021-09
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
multi-state system
dynamic Bayesian network
reliability
availability
maintenance optimization
Opis:
Nowadays, the main challenge in maintenance is to establish a dynamic maintenance strategy to significantly track and improve the performance measures of multi-state systems in terms of production, quality, security and even the environment. This paper presents a quantitative approach based on Dynamic Bayesian Network (DBN) to model and evaluate the maintenance of multi-state system and their functional dependencies. According to transition relationships between the system states modeled by the Markov process, a DBN model is established. The objective is to evaluate the reliability and the availability of the system with taking into account the impact of maintenance strategies (perfect repair and imperfect repair). Using the proposed approach, the dynamic probabilities of system states can be determined and the subsystems contributing to system failure can also be identified. A practical application is demonstrated by a case study of a blower system. Through the result of the diagnostic inference, to improve the performances of the blower, the critical components C, F, W, and P should be given more attention. The results indicate also that the perfect repair strategy can improve significantly the performances of the blower, while the imperfect repair strategy cannot degrade the performances in comparison to the perfect repair strategy. These results show the effectiveness of this approach in the context of a predictive evaluation process and in providing the opportunity to evaluate the impact of the choices made on the future measurement of systems performances. Finally, through diagnostic analysis, intervention management and maintenance planning are managed efficiently and optimally.
Źródło:
Management and Production Engineering Review; 2021, 13, 3; 3-14
2080-8208
2082-1344
Pojawia się w:
Management and Production Engineering Review
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Modelowanie stanów czynnościowych w języku sieci bayesowskich
Modelling of functional statuses in the language of Bayesian networks
Autorzy:
Pawlak, H.
Maksym, P.
Powiązania:
https://bibliotekanauki.pl/articles/287368.pdf
Data publikacji:
2008
Wydawca:
Polskie Towarzystwo Inżynierii Rolniczej
Tematy:
wiedza
sieć bayesowska
model komputerowy
knowledge
Bayesian network
computer model
Opis:
Zastosowanie sieci bayesowskiej do modelowania stanów czynnościowych przedstawiono z perspektywy budowania komputerowego systemu reprezentacji wiedzy. Budowę modelu poprzedzono opracowaniem grafu stanów i przejść zmian pozycji ciała przy wykonywaniu czynności roboczych związanych pakowaniem serków homogenizowanych.
The use of a Bayesian network for modelling of functional statuses has been shown from the perspective of construction of a computerised knowledge representation system. The model construction was preceded with the development of a graph of statuses and transitions of body position changes while carrying out work operations involved in cream cheese packaging.
Źródło:
Inżynieria Rolnicza; 2008, R. 12, nr 7(105), 7(105); 173-177
1429-7264
Pojawia się w:
Inżynieria Rolnicza
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:
Evaluating dropout placements in Bayesian regression ResNet
Autorzy:
Shi, Lei
Copot, Cosmin
Vanlanduit, Steve
Powiązania:
https://bibliotekanauki.pl/articles/2147115.pdf
Data publikacji:
2022
Wydawca:
Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Tematy:
regression
Bayesian Neural Network
MC Dropout
Opis:
Deep Neural Networks (DNNs) have shown great success in many fields. Various network architectures have been developed for different applications. Regardless of the complexities of the networks, DNNs do not provide model uncertainty. Bayesian Neural Networks (BNNs), on the other hand, is able to make probabilistic inference. Among various types of BNNs, Dropout as a Bayesian Approximation converts a Neural Network (NN) to a BNN by adding a dropout layer after each weight layer in the NN. This technique provides a simple transformation from a NN to a BNN. However, for DNNs, adding a dropout layer to each weight layer would lead to a strong regularization due to the deep architecture. Previous researches [1, 2, 3] have shown that adding a dropout layer after each weight layer in a DNN is unnecessary. However, how to place dropout layers in a ResNet for regression tasks are less explored. In this work, we perform an empirical study on how different dropout placements would affect the performance of a Bayesian DNN. We use a regression model modified from ResNet as the DNN and place the dropout layers at different places in the regression ResNet. Our experimental results show that it is not necessary to add a dropout layer after every weight layer in the Regression ResNet to let it be able to make Bayesian Inference. Placing Dropout layers between the stacked blocks i.e. Dense+Identity+Identity blocks has the best performance in Predictive Interval Coverage Probability (PICP). Placing a dropout layer after each stacked block has the best performance in Root Mean Square Error (RMSE).
Źródło:
Journal of Artificial Intelligence and Soft Computing Research; 2022, 12, 1; 61--73
2083-2567
2449-6499
Pojawia się w:
Journal of Artificial Intelligence and Soft Computing Research
Dostawca treści:
Biblioteka Nauki
Artykuł
Wyświetlanie 1-15 z 54

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