Wyniki wyszukiwania - Biblioteka Nauki

1

A holistic framework for conceptualising and describing risk

100%

Aven T.

Journal of Polish Safety and Reliability Association

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2010

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tom Vol. 1, No. 1

7--14

EN

A number of definitions and interpretations of the risk concept exist. Many of these are probability-based. In this paper we present and discuss a structure for characterising the definitions, which is founded on a clear distinction between (a) risk as a concept based on events, consequences and uncertainties; (b) risk as a modelled, quantitative concept; and (c) risk descriptions. The discussion leads to a holistic framework for conceptualising and assessing risk, which is based on risk defined by (a), and the probability-based definitions of risk can be viewed as related model parameters and/or risk descriptions. Two ways of detailing the framework are outlined: the relative frequency-based approach and the Bayesian approach. The Framework provides clear guidance on how to think when conceptualising and assessing risk in practice. Such guidance is strongly needed for the risk analysis discipline which is young and characterised by many different risk perspectives and approaches.

2

Bayesian graphical model based optimal decision-making for fault diagnosis of critical induction motors in industrial applications

88%

Lakehal A.

Bulletin of the Polish Academy of Sciences. Technical Sciences

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2020

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tom Vol. 68, nr 3

467--476

EN

In an effort to achieve an optimal availability time of induction motors via fault probabilities reduction and improved prediction or diagnostic tools responsiveness, a conditional probabilistic approach was used. So, a Bayesian network (BN) has been developed in this paper. The objective will be to prioritize predictive and corrective maintenance actions based on the definition of the most probable fault elements and to see how they serve as a foundation for the decision framework. We have explored the causes of faults for an induction motor. The influence of different power ranges and the criticality of the electric induction motor are also discussed. With regard to the problem of induction motor faults monitoring and diagnostics, each technique developed in the literature concerns one or two faults. The model developed, through its unique structure, is valid for all faults and all situations. Application of the proposed approach to some machines shows promising results on the practical side. The model developed uses factual information (causes and effects) that is easy to identify, since it is best known to the operator. After that comes an investigation into the causal links and the definition of the a priori probabilities. The presented application of Bayesian networks is the first of its kind to predict faults of induction motors. Following the results of the inference obtained, prioritizations of the actions can be carried out.

3

The Effect of CAP Subsidies on the Technical Efficiency of Polish Dairy Farms

88%

Marzec J. , Pisulewski A.

Central European Journal of Economic Modelling and Econometrics

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2017

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nr 3

4

A Bayesian virtual metrology for quality inspection of mobile repeater systems

88%

Kim S. D. , Kim J. S. , Mun B. M. , Bae S. J.

Management and Production Engineering Review

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2016

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tom Vol. 7, No. 4

48--53

EN

The technology of wideband code division multiple access (WCDMA) has been applied to band selective interference cancellation system (ICS) repeaters. To inspect the telecommunication quality of the systems, quality engineers must check the shape of the signals at the corresponding frequency band of the repeaters. However, measuring the signal quality is a repetitive manual task which requires much inspection time and high costs. In the case of small-sized samples, such as the example of an ICS repeater system, Bayesian approaches have been employed to improve the estimation accuracy by incorporating prior information on the parameters of the model in consideration. This research proposes a virtual method of quality inspection for products using a correlation structure of measurement data, mainly in a Bayesian regression framework. The Bayesian regression model derives prior information from historical measurement data to predict measurements of other frequency bandwidths by exploiting the correlation structure of each measurement data. Empirical results show the potential for reducing inspection costs and time by predicting the values of adjoining frequency bandwidths through measured data of a frequency bandwidth in the course of quality inspections of ICS repeater systems.

5

Comparing particulate matter dispersion in Thailand using the Bayesian Confidence Intervals for ratio of coefficients of variation

88%

Thangjai W. , Niwitpong S.

Statistics in Transition new series

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2020

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tom 21

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nr 5

41-60

XX

Recently, harmful levels of air pollution have been detected in many provinces of Thailand. Particulate matter (PM) contains microscopic solids or liquid droplets that are so small that they can be inhaled and cause serious health problems. A high dispersion of PM is measured by a coefficient of variation of log-normal distribution. Since the log-normal distribution is often used to analyse environmental data such as hazardous dust particle levels and daily rainfall data. These data focus the statistical inference on the coefficient of variation. In this paper, we develop confidence interval estimation for the ratio of coefficients of variation of two log-normal distributions constructed using the Bayesian approach. These confidence intervals were then compared with the existing approaches: method of variance estimates recovery (MOVER), modified MOVER, and approximate fiducial approaches using their coverage probabilities and average lengths via Monte Carlo simulation. The simulation results show that the Bayesian confidence interval performed better than the others in terms of coverage probability and average length. The proposed approach and the existing approaches are illustrated using examples from data set PM10 level and PM2.5 level in the northern Thailand.

6

Podejście Bayesa w przemysłowych systemach kontroli i sterowania przy wykorzystaniu tomografii procesowej

75%

Romanowski A. , Grudzień K. , Williams R. A. , Aykroyd R. A. , West R. M. , Meng S.

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2004

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tom T. 8, z. 3

217-222

PL

Technika pomiarowa, jaką jest tomografia procesowa, stanowi unikalne narzędzie do monitorowania stanu i informowania o szeregu procesów przemysłowych, zważywszy na fakt, że jest ona nieinwazyjna, a więc jej użycie nie zaburza samego procesu. Jednakże przykłady prób opracowania przy jej użyciu systemów kontroli i sterowania nadal obarczone są szeregiem niedoskonałości. Większość dotychczas proponowanych rozwiązań skupia się na rekonstrukcji obrazów pochodzących z tomograficznych danych pomiarowych, a następnie na ich postprocesingu. Niestety klasyczne metody rekonstrukcji obrazów są obciążone trudnymi do oszacowania błędami, które prowadzą do bezpowrotnej utraty części informacji. Natomiast zastosowanie teorii Bayesa daje większą elastyczność analizy danych pomiarowych, możliwość zawarcia dodatkowej wiedzy a priori w fazie obróbki danych oraz, co najważniejsze, umożliwia bezpośrednie szacowanie dowolnie wybranych parametrów procesu z pominięciem etapu rekonstrukcji.

EN

Process tomography as a measurement and exploration tool gives a unique chance of investigation/monitoring/control the industrial processes without interrupting the process since it is nonintrusive by definition. Unfortunately the so far proposed methods of ECT based industrial process control systems failed to be efficient and automatic. These systems were associated with image reconstruction techniques which introduce unquantified errors and lead to loss of information. Bayesian approach presented here is more flexible in output modelling, allows incorporating prior knowledge into data processing and gives the opportunity for direct desired parameters estimation.

7

X-ray Computed Tomography using a Sparsity Enforcing Prior Model Based on Haar Transformation in a Bayesian Framework

75%

Wang L. , Mohammad-Djafari A. , Gac N.

Fundamenta Informaticae

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2017

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tom Vol. 155, nr 4

449--480

EN

X-ray Computed Tomography (CT) has become a hot topic in both medical and industrial applications in recent decades. Reconstruction by using a limited number of projections is a significant research domain. In this paper, we propose to solve the X-ray CT reconstruction problem by using the Bayesian approach with a hierarchical structured prior model basing on the multilevel Haar transformation. In the proposed model, the multilevel Haar transformation is used as the sparse representation of a piecewise continuous image, and a generalized Student-t distribution is used to enforce its sparsity. The simulation results compare the performance of the proposed method with some state-of-the-art methods.

8

Evaluation of the financial condition of companies after the announcement of arrangement bankruptcy: application of the classical and Bayesian logistic regression

75%

Pawełek B. , Kostrzewska J. , Kostrzewski M. , Gałuszka K.

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nr 1

5-32

EN

The aim of this paper is to present the results of an assessment of the financial condition of companies from the construction industry after the announcement of arrangement bankruptcy, in comparison to the condition of healthy companies. The logistic regression model estimated by means of the maximum likelihood method and the Bayesian approach were used. The first achievement of our study is the assessment of the financial condition of companies from the construction industry after the announcement of bankruptcy. The second achievement is the application of an approach combining the classical and Bayesian logistic regression models to assess the financial condition of companies in the years following the declaration of bankruptcy, and the presentation of the benefits of such a combination. The analysis described in the paper, carried out in most part by means of the ML logistic regression model, was supplemented with information yielded by the application of the Bayesian approach. In particular, the analysis of the shape of the posterior distribution of the repeat bankruptcy probability makes it possible, in some cases, to observe that the financial condition of a company is not clear, despite clear assessments made on the basis of the point estimations.

9

Bayesian SVLEDEJ Model for Detecting Jumps in Logarithmic Growth Rates of One Month Forward Gas Contract Prices

75%

Kostrzewski M.

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nr 3

10

Simulation based verification of the Bayesian approach in single-pool hemodialysis modelling

75%

Korohoda P.

Bio-Algorithms and Med-Systems

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2010

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tom Vol. 6, no. 12

105--111

EN

In the paper an intensive computational comparative study has been described. With use of a hundred thousand pseudo-randomly generated hemodialysis sessions, a comparison between the efficiency of the Bayesian approach and the classic RMSE optimisation used in the urea kinetic modelling has been performed. The studied procedure of kinetic modelling utilized asingle-pool model to find from a number of measured urea concentration values: a) clearance K, b) generation rate G, c) distribution volume V. The obtained results indicate that the Bayesian approach, while in general being better than the classic one, is very sensitive to errors in the assumed a priori distributions parameters, and in such cases it may also lead to considerably unreliable results. Additionally, a strong critique emerged against the classic optimisation used for the studied task. The above observations indicate a need to design a specific optimisation technique, relevantly suited for the studied problem.

PL

W artykule opisano intensywne obliczeniowe studium porównawcze. Z wykorzystaniem stu tysięcy symulowanych sesji hemodializy skonfrontowano efektywność zastosowania w modelowaniu kinetycznym mocznika klasycznej optymalizacji z minimalizacją błędu średniokwadratowego i podejścia bayesowkiego. Poddana badaniom procedura modelowania kinetycznego wykorzystywała model jednokompartmentowy w celu wyznaczenia, na podstawie kilku wartości stężenia mocznika, następujących parametrów: a) klirensu K, b) tempa generacji G oraz c) objętości dystrybucji V. Uzyskane wyniki wykazały, iż podejście bayesowkie, chociaż generalnie lepsze od klasycznego, jest bardzo wrażliwe na błędy w założonych parametrach rozkładów i w takim przypadku może prowadzić do wyników w znacznym stopniu niewiarygodnych. Ponadto stwierdzono, że należy poddać poważnej krytyce klasyczną metodę optymalizacji, stosowaną typowo do postawionego zadania. Obserwacje te wskazują na konieczność opracowania nowej metody, odpowiednio dostosowanej do rozważanego zagadnienia.

11

Advantage of Bayesian approach to geotechnical designing

75%

Garbulewski K. , Jablonowski S. , Rabarijoely S.

Annals of Warsaw University of Life Sciences - SGGW. Land Reclamation

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2009

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tom 41

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nr 2

83-93

12

Proposing Probabilistic Operational Risk Assessment Model for Textile Industry Using Bayesian Approach

63%

Jan M. , Khalid M. S. , Awan A. A. , Nisar S.

Fibres & Textiles in Eastern Europe

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2018

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tom Vol. 26, no. 1 (127)

10--20

EN

Accidents, operational failures and losses prompt authorities to highlight the importance of adequate systems and controls to deal with operational risk (OR). Therefore risk assessment methodology has become a dire need of major industries for undertaking valuable measured in production and operation’s research. The paper describes methodology for conducting the risk assessment of the textile operational domain in general i.e. developing a conceptual risk assessment framework and conducting the methodological implementation of the selected operational risk element using the approach proposed. The risk assessment model proposed embraces the concept of probabilistic risk assessment structural modeling using the Bayesian Approach in its generalised form that may be applied to specific textile operational settings with the definition of dimensions and scales for a specific textile environment. The generalised model proposed can also be applied to different textile industries with the insertion of real data for testing and validation. The OR prediction model proposed is GUI-based, scalable, expandable and can be tested for any textile operations with little modification in parentend nodes under the specific risk element. The paper is helpful to ensure safety and a pro-active approach in textile risk management and also contributes towards the sustainable development of industry operations in the future.

PL

Wypadki, awarie i straty operacyjne skłaniają do podkreślenia znaczenia odpowiednich systemów i mechanizmów kontroli w celu radzenia sobie z ryzykiem operacyjnym (OR). W artykule opisano metodologię przeprowadzania oceny ryzyka w zakresie ogólnej działalności włókienniczej, tj. opracowanie ram koncepcyjnej oceny ryzyka i przeprowadzenie metodycznej realizacji wybranego elementu ryzyka operacyjnego z wykorzystaniem proponowanego podejścia. Proponowany model oceny ryzyka obejmuje koncepcję modelowania strukturalnego probabilistycznej oceny ryzyka z wykorzystaniem podejścia bayesowskiego w swojej uogólnionej formie, która może być stosowana do określonych ustawień operacyjnych wyrobów włókienniczych z definicją wymiarów i skal dla określonego środowiska włókienniczego. Proponowany ogólny model może również znaleźć zastosowanie w różnych branżach tekstylnych, wprowadzając rzeczywiste dane do testowania i walidacji. Proponowany model prognozowania OR, oparty na interfejsie GUI, jest skalowalny, rozszerzalny i może być zastosowany w przypadku dowolnych operacji z niewielkimi modyfikacjami w węzłach nadrzędnych/końcowych w ramach określonego elementu ryzyka. Dane zaprezentowane w artykule mogą być przydatne w zakresie zarządzania ryzykiem włókienniczym, a także wnoszą wkład do zrównoważonego rozwoju działalności przemysłowej w przyszłości.

13

Outside the box : an alternative data analytics framework

63%

Angelov P.

Journal of Automation Mobile Robotics and Intelligent Systems

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2014

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tom Vol. 8, No. 2

29--35

EN

In this paper, an alternative framework for data analytics is proposed which is based on the spatially-aware concepts of eccentricity and typicality which represent the density and proximity in the data space. This approach is statistical, but differs from the traditional probability theory which is frequentist in nature. It also differs from the belief and possibility-based approaches as well as from the deterministic first principles approaches, although it can be seen as deterministic in the sense that it provides exactly the same result for the same data. It also differs from the subjective expert-based approaches such as fuzzy sets. It can be used to detect anomalies, faults, form clusters, classes, predictive models, controllers. The main motivation for introducing the new typicality- and eccentricity-based data analytics (TEDA) is the fact that real processes which are of interest for data analytics, such as climate, economic and financial, electro-mechanical, biological, social and psychological etc., are often complex, uncertain and poorly known, but not purely random. Unlike, purely random processes, such as throwing dices, tossing coins, choosing coloured balls from bowls and other games, real life processes of interest do violate the main assumptions which the traditional probability theory requires. At the same time they are seldom deterministic (more precisely, have always uncertainty/noise component which is nondeterministic), creating expert and belief-based possibilistic models is cumbersome and subjective. Despite this, different groups of researchers and practitioners favour and do use one of the above approaches with probability theory being (perhaps) the most widely used one. The proposed new framework TEDA is a systematic methodology which does not require prior assumptions and can be used for development of a range of methods for anomalies and fault detection, image processing, clustering, classification, prediction, control, filtering, regression, etc. In this paper due to the space limitations, only few illustrative examples are provided aiming proof of concept.

14

Pomiar efektywności zróżnicowanych technologicznie gospodarstw rolnych w Unii Europejskiej

63%

Marzec J. , Pisulewski A.

Gospodarka Narodowa. The Polish Journal of Economics

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2020

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tom 303

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nr 3

111-137

EN

The aim of the present study was to derive the characteristics of the production process for crop farms in the European Union member states. The paper uses regional data on farms taken from the Farm Accountancy Data Network (FADN). Therefore, the models that account for heterogeneity among the analysed regions, were used in the present study. In particular, the paper considers two approaches to modelling heterogeneity: deterministic and stochastic. The deterministic approach is reflected in the paper with the usage of translog production function model, which allows output elasticities to depend on the input levels. The stochastic approach is represented by a stochastic frontier model with random coefficients. The application of the above-mentioned concept allowed to derive the Cobb-Douglas (C–D) production function model with individual parameters. The parameters of the four models were estimated using the Bayesian approach. The obtained results indicate that the C–D model is the best. In addition, it was observed that for the EU average, the highest production elasticity is with respect to materials, while the lowest w.r.t area. Surprisingly, the results suggest a high mean technical efficiency of the analysed regions (0.95), with very small dispersion of these scores.

PL

Celem niniejszego opracowania jest określenie charakterystyk procesu produkcyjnego gospodarstw rolnych specjalizujących się w uprawach polowych w państwach członkowskich Unii Europejskiej. W pracy wykorzystano dane regionalne FADN. W związku z występującym zróżnicowaniem między regionami w pracy wykorzystano modele uwzględniające tę heterogeniczność. W szczególności rozważono dwa sposoby modelowania heterogeniczności: deterministyczny oraz stochastyczny. Odzwierciedleniem pierwszego sposobu jest wykorzystanie w niniejszej pracy modelu funkcji produkcji typu translog, który pozwala, żeby elastyczności produkcji względem nakładów czynników produkcji zależały od wielkości nakładów. Natomiast stochastyczny sposób modelowania heterogeniczności reprezentuje stochastyczny model graniczny z losowymi parametrami. Zastosowanie powyższej koncepcji pozwoliło na zbudowanie modelu funkcji produkcji typu Cobba i Douglasa (C–D) z indywidualnymi parametrami. Estymacji parametrów czterech modeli dokonano za pomocą podejścia bayesowskiego. Otrzymane wyniki jednoznacznie wskazują, że najlepszym modelem okazał się model C–D z indywidualnymi parametrami. Ponadto zaobserwowano, że dla średniej unijnej najwyższa elastyczność produkcji występuje względem nakładów materiałów, a najniższa względem areału. Natomiast dosyć zaskakującym wynikiem jest wysoki poziom średniej efektywności technicznej (0,95) przy bardzo niewielkim rozproszeniu tych ocen.

15

Heuristics applying stochastic information as tools for thermoacoustic standing-wave engine optimization

51%

Nowak I.

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2018

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tom Vol. 25, no. 1

3--19

EN

In this article, two numerical methods for solving engineering problems defined as multicriteria optimiza-tion and inverse problem are presented. In particular, thisstudy deals with the optimization of the designof thermoacoustic engine in the frame in which both types of tasks are solved. The first proposed heuristicserves to find many p-optimal solutions simultaneously, which represents a compromise between usuallymutually contradictory goals at work. Based on them, the full Pareto front is approximated. The inverseproblem solution reproduces parameters for solutions located on a designated front but those that arenot found in multicriteria optimization. In this article, the RACO heuristics are proposed for determiningp-optimal solutions and the Bayesian approach is introduced as a method for solving ill-conditioned inverseproblems. Optimization of the construction of the thermoacoustic engine is aimed at verifying proposedmethodology and present the possibility of using both methods in engineering problems. The problemdiscussed in this article is formulated and the numerical methods used in the solution are presented indetails.

16

Charakterystyka geotechniczna osadów wysoczyzny morenowej na podstawie badań kampusu SGGW w Warszawie

38%

Rabarijoely S. , Lech M. , Bajda M. , Markowska-Lech K.

Przegląd Budowlany

|

2023

|

tom R. 94, nr 5-6

152--158

PL

W artykule, na przykładzie kampusu SGGW w Warszawie, przedstawione zostały kryteria identyfikacji warstw geotechnicznych na obszarze wysoczyzny morenowej, pozwalające na bardziej wiarygodną ocenę parametrów geotechnicznych poszczególnych warstw podłoża z uwzględnieniem lokalnych uwarunkowań. W pracy wykorzystano wyniki badań terenowych, głównie CPT oraz DMT, które porównano z wynikami badań laboratoryjnych pobranych próbek gruntów. Proponowana metoda podziału warstw geotechnicznych wraz z doborem odpowiednich parametrów gruntowych dla wydzielanych warstw zakłada zastosowanie podejścia bayesowskiego.

EN

The paper presents criteria for identification of geotechnical layers in the area of moraine upland, on the example of the Warsaw University of Life Sciences Campus - SGGW, which allows a more reliable assessment of the geotechnical parameters of individual ground layers, taking into account local conditions. The paper uses the results of in situ tests, mainly CPT and DMT, which were compared with the results of laboratory tests. A Bayesian approach was used in proposing a technique for subdividing the geotechnical layers with the annotation of the relevant parameters for the separated layers.