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Tytuł:
Prediction model of the pandemic spreading based on weibull distribution
Autorzy:
Guľáš, Ľuboš
Talian, Matej
Szabo, Stanislav
Semrádová, Beáta
Powiązania:
https://bibliotekanauki.pl/articles/2204124.pdf
Data publikacji:
2022
Wydawca:
STE GROUP
Tematy:
pandemics
prediction model
weibull distribution
Opis:
Pandemics have the potential to cause immense disruption of our everyday activities and has impact on the communities and societies mainly through the restrictions applied to the business activities, services, manufacturing, but also education, transportation etc. Therefore, it is important to create suitable prediction models to establish convenient methods for the planning of the operations and processes to cope with the difficulty. In this paper, the prediction model for the spread of the viral disease in term of the estimated maximal weekly confirmed cases and weekly deaths using the Weibull distribution as a theoretical model for statistical data processing is presented. The theoretical prediction model was applied and confirmed on the data available for the whole world and compared to the situation in Europe and Slovakia for the pandemic waves and can be used for the more precise prediction of the pandemic situation and to enhance planning of the activities and processes regarding to the restrictions applied during the worsening pandemic situation.
Źródło:
Management Systems in Production Engineering; 2022, 2 (30); 179--186
2299-0461
Pojawia się w:
Management Systems in Production Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Temperature and Humidity Data Evaluation of Tight Sportswear During Motion Based on Intelligent Modeling
Autorzy:
Cheng, Pengpeng
Wang, Jianping
Zeng, Xianyi
Bruniaux, Pascal
Chen, Daoling
Powiązania:
https://bibliotekanauki.pl/articles/24200969.pdf
Data publikacji:
2023
Wydawca:
Sieć Badawcza Łukasiewicz - Instytut Biopolimerów i Włókien Chemicznych
Tematy:
motion state
tight sportswear
temperature
humidity
prediction model
Opis:
A neural network structure of Long Short Term Memory (LSTM) is proposed which could be used to predict the temperaturę and humidity of other key parts from the temperature and humidity data of some parts of the human body when wearing tight sportswear, so as to realize the temperature and humidity data prediction of all key points of the human body. The temperaturę and humidity of different people wearing tights were collected by DHT sensors. The experimental results show that the LSTM neural network structure proposed has higher prediction accuracy than other algorithms, and the model evaluates the feasibility of temperature and humidity data of tights in a state of motion, which facilitates the study of dynamic thermal and humid comfort and reduces the time cost of analyzing the temperature and humidity distribution and changing the law during human movement. It will effectively promote the study of temperature and humidity changes when people wear sports tights, provide theoretical reference for the study of human skin temperature in the field of sports medicine, and provide practical guidance for the application of human skin temperature changes in sports clothing production, diagnosis and prevention of sports injuries.
Źródło:
Fibres & Textiles in Eastern Europe; 2023, 31, 3; 1--8
1230-3666
2300-7354
Pojawia się w:
Fibres & Textiles in Eastern Europe
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
On Woven Fabric Sound Absorption Prediction
Autorzy:
Prasetiyo, I.
Desendra, G.
Hermanto, M. N.
Adhika, D. R.
Powiązania:
https://bibliotekanauki.pl/articles/177484.pdf
Data publikacji:
2018
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
woven fabric
prediction model
sound absorber
building applications
Opis:
For building applications, woven fabrics have been widely used as finishing elements of room interior but not in particular aimed for sound absorbers. Considering the micro perforation of the woven fabrics, they should have potential to be used as micro-perforated panel (MPP) absorbers; some measurement results indicated such absorption ability. Hence, it is of importance to have a sound absorption model of the woven fabrics to enable us predicting their sound absorption characteristic that is beneficial in engineering design phase. Treating the woven fabric as a rigid frame, a fluid equivalent model is employed based on the formulation of Johnson-Champoux-Allard (JCA). The model obtained is then validated by measurement results where three kinds of commercially available woven fabrics are evaluated by considering their perforation properties. It is found that the model can reasonably predict their sound absorption coefficients. However, the presence of perturbations in pores give rise to inaccuracy of resistive component of the predicted surface impedance. The use of measured static flow resistive and corrected viscous length in the calculations are useful to cope with such a situation. Otherwise, the use of an optimized simple model as a function of flow resistivity is also applicable for this case.
Źródło:
Archives of Acoustics; 2018, 43, 4; 707-715
0137-5075
Pojawia się w:
Archives of Acoustics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Prognozowanie rynku usług transportowych
Forecasting of the transport market
Autorzy:
Cisowski, T.
Powiązania:
https://bibliotekanauki.pl/articles/253575.pdf
Data publikacji:
2015
Wydawca:
Instytut Naukowo-Wydawniczy TTS
Tematy:
prognozowanie
model predykcyjny
model przewozu
forecasting
prediction model
model of carriage
Opis:
W niniejszej pracy pokazano szeroką klasę modeli stosowanych w prognozowaniu wskaźników przewozów. Przedstawiono wielopoziomowe modele przewozów. Zaproponowano algorytm prognozowania przewozów na bazie analizy dynamiki procesów zachodzących w makroekonomicznym otoczeniu transportu kolejowego.
The paper presents the models used in forecasting transport indicators. Multilevel transport market models were discussed. The author proposed an algorithm for predicting carriage on the basis the assessment of the dynamics processes occurring in the macroeconomic environment of rail transport.
Źródło:
TTS Technika Transportu Szynowego; 2015, 1-2; 78-80
1232-3829
2543-5728
Pojawia się w:
TTS Technika Transportu Szynowego
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Choice of Functional Form for Independent Variables in Accident Prediction Models
Autorzy:
Kamińska, Joanna
Powiązania:
https://bibliotekanauki.pl/articles/504161.pdf
Data publikacji:
2014
Wydawca:
Międzynarodowa Wyższa Szkoła Logistyki i Transportu
Tematy:
accident prediction model
Poisson lognormal model
cumulative residuals
functional form
Opis:
The development of multivariate statistical models to identify factors that explain systematic variation in accident counts has been an active field of research in the past 20 years. During this period many different models and functional forms have been applied. This study, based on data for national roads in Norway, tests alternative functional forms of the relationship between independent variables and the number of injury accidents. The paper compares six different functional forms (sets of independent variables and specifications of the form of their relationship to accident occurrence) by means of Poisson-lognormal regression. The best model was identified in terms of five goodness of fit measures and a graphical method – the CURE plot (CURE = cumulative residuals). The coefficients estimated for the independent variables were found to vary according to functional form. It is therefore important to compare different functional forms as part of an exploratory analysis when developing accident prediction models.
Źródło:
Logistics and Transport; 2014, 21, 1; 51-62
1734-2015
Pojawia się w:
Logistics and Transport
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Bankruptcy prediction in Visegrad group countries using multiple discriminant analysis
Autorzy:
Kliestik, Tomas
Vrbka, Jaromir
Rowland, Zuzana
Powiązania:
https://bibliotekanauki.pl/articles/22446534.pdf
Data publikacji:
2018
Wydawca:
Instytut Badań Gospodarczych
Tematy:
bankruptcy
prediction model
discriminant analysis
Visegrad group
financial analysis
Opis:
Research background: The problem of bankruptcy prediction models has been a current issue for decades, especially in the era of strong competition in markets and a constantly growing number of crises. If a company wants to prosper and compete successfully in a market environment, it should carry out a regular financial analysis of its activities, evaluate successes and failures, and use the results to make strategic decisions about the future development of the business. Purpose of the article: The main aim of the paper is to develop a model to reveal the un-healthy development of the enterprises in V4 countries, which is done by the multiple discriminant analysis. Methods: To conduct the research, we use the Amadeus database providing necessary financial and statistical data of almost 450,000 enterprises, covering the year 2015 and 2016, operating in the countries of the Visegrad group. Realizing the multiple discriminant analysis, the most significant predictor and the best discriminants of the corporate prosperity are identified, as well as the prediction models for both individual V4 countries and complex Visegrad model. Findings & Value added: The results of the research reveal that the prediction models use the combination of same financial ratios to predict the future financial development of a company. However, the most significant predictors are current assets to current liabilities ratio, net income to total assets ratio, ratio of non-current liabilities and current liabilities to total assets, cash and cash equivalents to total assets ratio and return of equity. All developed models have more than 80 % classification ability, which indicates that models are formed in accordance with the economic and financial situation of the V4 countries. The research results are important for companies themselves, but also for their business partners, suppliers and creditors to eliminate financial and other corporate risks related to the un-healthy or unfavorable financial situation of the company.
Źródło:
Equilibrium. Quarterly Journal of Economics and Economic Policy; 2018, 13, 3; 569-593
1689-765X
2353-3293
Pojawia się w:
Equilibrium. Quarterly Journal of Economics and Economic Policy
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Bankruptcy prediction in the post-pandemic period: A case study of Visegrad Group countries
Autorzy:
Valaskova, Katarina
Gajdosikova, Dominika
Belas, Jaroslav
Powiązania:
https://bibliotekanauki.pl/articles/19322751.pdf
Data publikacji:
2023
Wydawca:
Instytut Badań Gospodarczych
Tematy:
bankruptcy
prediction model
multiple discriminant analysis
Visegrad group countries
Opis:
Research background: Effective monitoring of financial health is essential in the financial management of enterprises. Early studies to predict corporate bankruptcy were published at the beginning of the last century. The prediction models were developed with a significant delay even among the Visegrad group countries. Purpose of the article: The primary aim of this study is to create a model for predicting bankruptcy based on the financial information of 20,693 enterprises of all sectors that operated in the Visegrad group countries during the post-pandemic period (2020-2021) and identify significant predictors of bankruptcy. To reduce potential losses to shareholders, investors, and business partners brought on by the financial distress of enterprises, it is possible to use multiple discriminant analysis to build individual prediction models for each Visegrad group country and a complex model for the entire Visegrad group. Methods: A bankruptcy prediction model is developed using multiple discriminant analysis. Based on this model, prosperity is assessed using selected corporate financial indicators, which are assigned weights such that the difference between the average value calculated in the group of prosperous and non-prosperous enterprises is as large as possible. Findings & value added: The created models based on 6-14 financial indicators were developed using different predictor combinations and coefficients. For all Visegrad group countries, the best variable with the best discriminating power was the total indebtedness ratio, which was included in each developed model. These findings can be used also in other Central European countries where the economic development is similar to the analyzed countries. However, sufficient discriminant ability is required for the model to be used in practice, especially in the post-pandemic period, when the financial health and stability of enterprises is threatened by macroeconomic development and the performance and prediction ability of current bankruptcy prediction models may have decreased. Based on the results, the developed models have an overall discriminant ability greater than 88%, which may be relevant for academicians to conduct further empirical studies in this field.
Źródło:
Oeconomia Copernicana; 2023, 14, 1; 253-293
2083-1277
Pojawia się w:
Oeconomia Copernicana
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Medium- and long-term prediction of polar motion using weighted least squares extrapolation and vector autoregressive modeling
Autorzy:
Lei, Yu
Zhao, Danning
Guo, Min
Powiązania:
https://bibliotekanauki.pl/articles/27314482.pdf
Data publikacji:
2023
Wydawca:
Polska Akademia Nauk. Centrum Badań Kosmicznych PAN
Tematy:
polar motion
prediction model
weighted least squares
vector autoregressive
Opis:
This article presents the application of weighted least squares (WLS) extrapolation and vector autoregressive (VAR) modeling in polar motion prediction. A piecewise weighting function is developed for the least squares (LS) adjustment in consideration of the effect of intervals between observation and prediction epochs on WLS extrapolation. Furthermore, the VAR technique is used to simultaneously model and predict the residuals of xp, yp pole coordinates for WLS misfit. The simultaneous predictions of xp, yp pole coordinates are subsequently computed by the combination of WLS extrapolation of harmonic models for the linear trend, Chandler and annual wobbles, and VAR stochastic prediction of the residuals (WLS+VAR). The 365-day-ahead xp, yp predictions are compared with those generated by LS extrapolation+univariate AR prediction and LS extrapolation+VAR modeling. It is shown that the xp, yp predictions based on WLS+VAR taking into consideration both the interval effect and correlation between xp and yp outperform those generated by two others. The accuracies of the xp predictions are 13.97 mas, 18.47 mas, and 20.52 mas, respectively for the 150-, 270-, and 365-day horizon in terms of the mean absolute error statistics, 36%, 24.8%, and 33.5% higher than LS+AR, respectively. For the yp predictions, the 150-, 270-, and 365-day accuracies are 15.41 mas, 21.17 mas, and 21.82 mas respectively, 27.4%, 11.9%, and 21.8% higher than LS+AR respectively. Moreover, the absolute differences of the WLS+VAR predictions and observations are smaller than the differences from LS+VAR and LS+AR, which is practically important to practical and scientific users, although the improvement in accuracies is no more than 10% relative to LS+VAR. The further comparison with the predictions submitted to the 1st Earth Orientation Parameters Prediction Comparison Campaign (1st EOP PCC) shows that while the accuracy of the predictions within 30 days is comparable with that by the most accurate prediction techniques including neural networks and LS+AR participating in the campaign for xp, yp pole coordinates, the accuracy of the predictions up to 365 days into the future are better than accuracies by the other techniques except best LS+AR used in the EOP PCC. It is therefore concluded that the medium- and long-term prediction accuracy of polar motion can be improved by modeling xp, yp pole coordinates together.
Źródło:
Artificial Satellites. Journal of Planetary Geodesy; 2023, 58, 2; 42--55
2083-6104
Pojawia się w:
Artificial Satellites. Journal of Planetary Geodesy
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Decision tree based model of business failure prediction for Polish companies
Autorzy:
Durica, Marek
Frnda, Jaroslav
Svabova, Lucia
Powiązania:
https://bibliotekanauki.pl/articles/19090954.pdf
Data publikacji:
2019
Wydawca:
Instytut Badań Gospodarczych
Tematy:
decision trees
prediction model
financial ratios
business failure
Polish companies
Opis:
Research background: The issue of predicting the financial situation of companies is a relatively young field of economic research. Its origin dates back to the 30's of the 20th century, but constant research in this area proves the currentness of this topic even today. The issue of predicting the financial situation of a company is up to date not only for the company itself, but also for all stakeholders. Purpose of the article: The main purpose of this study is to create new prediction models by using the method of decision trees, in achieving sufficient prediction power of the generated model with a large database of real data on Polish companies obtained from the Amadeus database. Methods: As a result of the development of artificial intelligence, new methods for predicting financial failure of the company have been introduced into financial prediction analysis. One of the most widely used data mining techniques in this field is the method of decision trees. In the paper, we applied the CART and CHAID approach to create a model of predicting the financial difficulties of Polish companies. Findings & Value added: For the creation of the prediction model, a total of 37 financial and economic indicators of Polish companies were used. The resulting decision trees based prediction models for Polish companies reach a prediction power of more than 98%. The success of the classification for non-prosperous companies is more than 83%. The created decision tree-based prediction models are useful mainly for predicting the financial difficulties of Polish companies, but can also be used for companies in another country.
Źródło:
Oeconomia Copernicana; 2019, 10, 3; 453-469
2083-1277
Pojawia się w:
Oeconomia Copernicana
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Nonlinear damage accumulation of concrete subjected to variable amplitude fatigue loading
Autorzy:
Chen, Y.
Chen, X.
Bu, J.
Powiązania:
https://bibliotekanauki.pl/articles/201230.pdf
Data publikacji:
2018
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
nonlinear damage
variable amplitude loading
prediction model
concrete
uszkodzenia
model predykcji
beton
Opis:
To account for the load sequence effect, damage fatigue models with nonlinearity in propagation and accumulation have been developed. This paper reviews five classical nonlinear fatigue models used to predict the life times of concrete under variable amplitude loadings. Experimental results from literature are used to validate the five classical prediction models. It can be found that Hilsdorf and Kesler model yields unsafe or conservative predictions, and the other four models are more suitable for predicting life times of concrete. In this paper, the author used a new nonlinear damage model based on the nonlinear continuum damage mechanics to predict fatigue life of concrete. The model considers fatigue limit, loading parameters, the unseparable characteristics for the damage parameter and the load sequence effect. The validity of the nonlinear fatigue damage model is checked against tests from literature.
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2018, 66, 2; 157-163
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Using ALARO and AROME numerical weather prediction models for the derecho case on 11 August 2017
Autorzy:
Kolonko, Marcin
Szczęch-Gajewska, Małgorzata
Bochenek, Bogdan
Stachura, Gabriel
Sekuła, Piotr
Powiązania:
https://bibliotekanauki.pl/articles/2166586.pdf
Data publikacji:
2022
Wydawca:
Instytut Meteorologii i Gospodarki Wodnej - Państwowy Instytut Badawczy
Tematy:
derecho
mesocyclone convective system
mesoscale convective vortex
numerical weather prediction model
ALARO model
AROME model
Opis:
On average, a derecho occurs once a year in Poland while bow echoes happen several times per year. On 11 August 2017, severe meteorological phenomena were observed in Poland, including extremely strong wind gusts. We focused especially on the convective windstorm of a derecho type which occurred on that date in northern and north-western Poland. A rapidly moving mesoscale convective system (MCS) resulted in a bow echo, a mesoscale convective vortex (MCV), and finally fulfilled the criteria for a derecho. To establish whether our operational models in the Institute of Meteorology and Water Management, National Research Institute (IMGW-PIB) could reproduce a derecho of such intensity as that of 11 August 2017, the results from two mesoscale numerical weather prediction models were analyzed. The Application of Research to Operation at Mesoscale (AROME) and the ALADIN & AROME (ALARO) models were applied in the non-hydrostatic regime. We also examine how models differ with respect to mesoscale convective system drivers (such as vertical wind shear and convective available potential energy) and representation of deep convection (e.g., vertical velocities, cold pool generation). Forecasts are compared with observations of wind gusts and radar data. Severe weather phenomena, such as rear inflow jet and cold pool, were predicted by both models, visible on the maps of the wind velocity at 850 and 925 hPa pressure levels and on the map of air temperature at 2 m above the ground level, respectively. Relative vorticity maps of the middle and lower troposphere were analyzed for understanding the evolution of MCV.
Źródło:
Meteorology Hydrology and Water Management. Research and Operational Applications; 2022, 10, 2; 1--25
2299-3835
2353-5652
Pojawia się w:
Meteorology Hydrology and Water Management. Research and Operational Applications
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Measurement data processing with the use of art networks
Przetwarzania danych pomiarowych z wykorzystaniem sieci z rezonansem adaptacyjnym ART
Autorzy:
Mrówczyńska, M.
Sztubecki, J.
Powiązania:
https://bibliotekanauki.pl/articles/970998.pdf
Data publikacji:
2018
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
ART neural network
prediction model
vertical displacements
sieci neuronowe ART
model predykcyjny
przemieszczenia pionowe
Opis:
ART (Adaptive Resonance Theory) networks were invented in the 1990s as a new approach to the problem of image classification and recognition. ART networks belong to the group of resonance networks, which are trained without supervision. The paper presents the basic principles for creating and training ART networks, including the possibility of using this type of network for solving problems of predicting and processing measurement data, especially data obtained from geodesic monitoring. In the first stage of the process of creating a prediction model, a preliminary analysis of measurement data was carried out. It was aimed at detecting outliers because of their strong impact on the quality of the final model. Next, an ART network was used to predict the values of the vertical displacements of points of measurement and control networks stabilized on the inner and outer walls of an engineering object.
Sieci neuronowe ART (ang. Adaptive Resonance Theory) zostały opracowane w latach 90 ubiegłego wieku, jako nowe podejście w rozwiązywaniu problemów klasyfikacji i rozpoznawaniu obrazów. Sieci ART należą do grupy sieci rezonansowych, których uczenie prowadzone jest w trybie nie nadzorowanym. W artykule przedstawiono podstawowe zasady budowy i uczenia sieci neuronowych ART wraz z możliwością aplikacji tego rodzaju sieci do rozwiązywania zagadnień predykcji i przetwarzania danych pomiarowych, w szczególności pozyskanych w wyniku prowadzonego monitoringu geodezyjnego. W pierwszym etapie procesu budowy modelu predykcyjnego wykonano wstępną analizę danych pomiarowych związaną z wykrywaniem obserwacji odstających ze względu na ich istotny wpływ na ostateczną jakość modelu. Następnie wykorzystując sieć ART wyznaczono przewidywane wartości przemieszczeń pionowych dla punktów sieci pomiarowo-kontrolnej, zastabilizowanych na wewnętrznych i zewnętrznych ścianach obiektu budowlanego, na których zauważono liczne spękania.
Źródło:
Civil and Environmental Engineering Reports; 2018, No. 28(2); 186-195
2080-5187
2450-8594
Pojawia się w:
Civil and Environmental Engineering Reports
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Intelligent Prediction Model of the Thermal and Moisture Comfort of the Skin-Tight Garment
Autorzy:
Cheng, Pengpeng
Wang, Jianping
Zeng, Xianyi
Bruniaux, Pascal
Chen, Daoling
Powiązania:
https://bibliotekanauki.pl/articles/2056304.pdf
Data publikacji:
2022
Wydawca:
Sieć Badawcza Łukasiewicz - Instytut Biopolimerów i Włókien Chemicznych
Tematy:
sportswear tights
thermal comfort
moisture comfort
principal component analysis
intelligent prediction model
Opis:
In order to improve the efficiency and accuracy of predicting the thermal and moisture comfort of skin-tight clothing (also called skin-tight underwear), principal component analysis (PCA) is used to reduce the dimensions of related variables and eliminate the multicollinearity relationship among variables. Then, the optimized variables are used as the input parameters of the coupled intelligent model of the genetic algorithm (GA) and back propagation (BP) neural network, and the thermal and moisture comfort of different tights (tight tops and tight trousers) under different sports conditions is analysed. At the same time, in order to verify the superiority of the genetic algorithm and BP neural network intelligent model, the prediction results of GA-BP, PCA-BP and BP are compared with this model. The results show that principal component analysis (PCA) improves the accuracy and adaptability of the GA-BP neural network in predicting thermal and humidity comfort. The forecasting effect of the PCA-GA-BP neural network is obviously better than that of the GA-BP, PCA-BP, BP model, which can accurately predict the thermal and moisture comfort of tight-fitting sportswear. The model has better forecasting accuracy and a simpler structure.
Źródło:
Fibres & Textiles in Eastern Europe; 2022, 1 (151); 50--58
1230-3666
2300-7354
Pojawia się w:
Fibres & Textiles in Eastern Europe
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Factors affecting the conclusion of an arrangement in restructuring proceedings: evidence from Poland
Autorzy:
Prusak, Błażej
Zaremba, Ulyana
Galiński, Paweł
Powiązania:
https://bibliotekanauki.pl/articles/28862021.pdf
Data publikacji:
2023
Wydawca:
Uniwersytet im. Adama Mickiewicza w Poznaniu
Tematy:
financial distress
preventive restructuring
turnaround prediction model
bankruptcy prediction
law & economics
Digital Poland of Equal Opportunities
Opis:
The EU Restructuring Directive (2019/1023) requires Member States to provide a preventive restructuring framework for financially distressed entities that remain viable or are likely to readily restore economic viability. The first step to a successful restructuring is the approval of an arrangement between the debtor and creditors. The main research objective of the article is to identify factors affecting the conclusion of an arrangement in restructuring proceedings. In the process of filtering companies initiating a restructuring procedure, these factors are seen as increasing the probability of concluding an arrangement between debtor and creditors. Moreover, an additional research objective is to construct a turnaround prediction model aimed at assessing the probability of a conclusion of an arrangement in restructuring proceedings. The study covered the companies in Poland for which restructuring proceedings opened between 2016 and 2021 ended with the approval of an arrangement, and a similar number of companies that failed to restructure successfully. Binary logistic regression was applied to achieve the aims of this study. The results show that two financial variables affected companies in terms of their chances to conclude the arrangement: the current ratio and return on assets were among the statistically significant indicators and they are characterized by higher values for debtors reaching the arrangement with their creditors. A direct positive relationship was also identified between the company’s lifespan and the outcome of the proceedings. The probability of the conclusion of the arrangement was also affected by the type of industry. Models assessing the probability of completing restructuring proceedings with an arrangement can be useful for insolvency practitioners and financial analysts during viability assessments.
Źródło:
Ruch Prawniczy, Ekonomiczny i Socjologiczny; 2023, 85, 3; 235-257
0035-9629
2543-9170
Pojawia się w:
Ruch Prawniczy, Ekonomiczny i Socjologiczny
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Work Efficiency Prediction of Persons Working in Traffic Noise Environment Using Adaptive Neuro Fuzzy Inference System (ANFIS) Models
Autorzy:
Yadav, Manoj
Tandel, Bhaven
Powiązania:
https://bibliotekanauki.pl/articles/2141713.pdf
Data publikacji:
2021
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
traffic noise
noise exposure
social questionnaire survey
human work efficiency
ANFIS prediction model
Opis:
A study was carried to assess the effect of traffic noise pollution on the work efficiency of shopkeepers in Indian urban areas. For this, an extensive literature survey was done on previous research done on similar topics. It was found that personal characteristics, noise levels in an area, working conditions of shopkeepers, type of task they are performing are the most significant factors to study effects on work efficiency. Noise monitoring, as well as a questionnaire survey, was done in Surat city to collect desired data. A total of 17 parameters were considered for assessing work efficiency under the influence of traffic noise. It is recommended that not more than 6 parameters should be considered for ANFIS modeling hence, before opting for the ANFIS modeling, most affecting parameters to work efficiency under the influence of traffic noise, was chosen by Structural Equation Model (SEM). As a result of the SEM model, two ANFIS prediction models were developed to predict the effect on work efficiency under the influence of traffic noise. R squared for model 1, for training data was 0.829 and for testing data, it was 0.727 and R squared for model 2 for training data was 0.828 and for testing data, it was 0.728. These two models can be used satisfactorily for predicting work efficiency under traffic noise environment for open shutter shopkeepers in tier II Indian cities.
Źródło:
Archives of Acoustics; 2021, 46, 4; 677-683
0137-5075
Pojawia się w:
Archives of Acoustics
Dostawca treści:
Biblioteka Nauki
Artykuł
Wyświetlanie 1-15 z 136

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