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Wyświetlanie 1-15 z 44
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:
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:
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:
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
Tytuł:
An expert elicitation analysis for vessel allision risk near the offshore wind farm by using fuzzy rule-based bayesian network
Autorzy:
Yu, Q.
Liu, K.
Powiązania:
https://bibliotekanauki.pl/articles/117215.pdf
Data publikacji:
2019
Wydawca:
Uniwersytet Morski w Gdyni. Wydział Nawigacyjny
Tematy:
offshore wind farms
expert elicitation analysis
Bayesian network model
fuzzy rule-based bayesian network
Failure Modes and Effects Analyses (FMEA)
Bayesian Networks
vessel allision risk
risk analysis
Opis:
This paper develops an expert based framework for analysing and synthesising the ship allision risk near the offshore wind farm (OWF) on the basis of a generic Fuzzy Bayesian network and FMEA analysis. This framework is specifically intended to overcome the difficulty of using traditional risk assessment methods in OWF allision. Under the introduced framework, subjective belief degrees are assigned to model the incompleteness encountered in establishing the knowledge base. The fuzzy transformation technology is then used to introduce all judgements results under various situations. Fully, a Bayesian network is established to aggregate all relevant attributes to the conclusion and to prioritise potential allision risk level of each ship categories. A series of case studies of different ship categories are studied to illustrate the application of the proposed framework. Results show that the fishing vessel and the service vessel have a higher allision risk than the merchant vessel due to insufficient risk detection. The collision consequence of the tanker is significantly higher than other types of vessel. The framework facilitates subjective risk assessment when historical failure data is not available in their practice, which provides support to OWF-safeguarding and decision-making.
Źródło:
TransNav : International Journal on Marine Navigation and Safety of Sea Transportation; 2019, 13, 4; 831-837
2083-6473
2083-6481
Pojawia się w:
TransNav : International Journal on Marine Navigation and Safety of Sea Transportation
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A model for oil spill scenarios from tanker collision accidents in the Northern Baltic Sea
Autorzy:
Goerlandt, F.
Powiązania:
https://bibliotekanauki.pl/articles/135392.pdf
Data publikacji:
2017
Wydawca:
Akademia Morska w Szczecinie. Wydawnictwo AMSz
Tematy:
oil spill
collision
maritime safety
marine environment
risk assessment
Bayesian Network
Opis:
Oil spills from maritime activities can lead to very extensive damage to the marine environment and disrupt maritime ecosystem services. Shipping is an important activity in the Northern Baltic Sea, and with the complex and dynamic ice conditions present in this sea area, navigational accidents occur rather frequently. Recent risk analysis results indicate those oil spills are particularly likely in the event of collisions. In Finnish sea areas, the current wintertime response preparedness is designed to a level of 5000 tonnes of oil, whereas a state-of-the-art risk analysis conservatively estimates that spills up to 15000 tonnes are possible. Hence, there is a need to more accurately estimate oil spill scenarios in the Northern Baltic Sea, to assist the relevant authorities in planning the response fleet organization and its operations. An issue that has not received prior consideration in maritime waterway oil spill analysis is the dynamics of the oil outflow, i.e. how the oil outflow extent depends on time. Hence, this paper focuses on time-dependent oil spill scenarios from collision accidents possibly occurring to tankers operating in the Northern Baltic Sea. To estimate these, a Bayesian Network model is developed, integrating information about designs of typical tankers operating in this area, information about possible damage scenarios in collision accidents, and a state-of-the-art time-domain oil outflow model. The resulting model efficiently provides information about the possible amounts of oil spilled in the sea in different periods of time, thus contributing to enhanced oil spill risk assessment and response preparedness planning.
Źródło:
Zeszyty Naukowe Akademii Morskiej w Szczecinie; 2017, 50 (122); 9-20
1733-8670
2392-0378
Pojawia się w:
Zeszyty Naukowe Akademii Morskiej w Szczecinie
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Bayesian Network Based Fault Tolerance in Distributed Sensor Networks
Autorzy:
Lokesh, B. B.
Nalini, N.
Powiązania:
https://bibliotekanauki.pl/articles/308287.pdf
Data publikacji:
2014
Wydawca:
Instytut Łączności - Państwowy Instytut Badawczy
Tematy:
Bayesian network
distributed sensor networks
fault detection
fault tolerance
fault recovery
network control
routing
Opis:
A Distributed Sensor Network (DSN) consists of a set of sensors that are interconnected by a communication network. DSN is capable of acquiring and processing signals, communicating, and performing simple computational tasks. Such sensors can detect and collect data concerning any sign of node failure, earthquakes, floods and even a terrorist attack. Energy efficiency and fault-tolerance network control are the most important issues in the development of DSNs. In this work, two methods of fault tolerance are proposed: fault detection and recovery to achieve fault tolerance using Bayesian Networks (BNs). Bayesian Network is used to aid reasoning and decision making under uncertainty. The main objective of this work is to provide fault tolerance mechanism which is energy efficient and responsive to network using BNs. It is also used to detect energy depletion of node, link failure between nodes, and packet error in DSN. The proposed model is used to detect faults at node, sink and network level faults (link failure and packet error). The proposed fault recovery model is used to achieve fault tolerance by adjusting the network of the randomly deployed sensor nodes based on of its probabilities. Finally, the performance parameters for the proposed scheme are evaluated.
Źródło:
Journal of Telecommunications and Information Technology; 2014, 4; 44-52
1509-4553
1899-8852
Pojawia się w:
Journal of Telecommunications and Information Technology
Dostawca treści:
Biblioteka Nauki
Artykuł
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