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Wyświetlanie 1-15 z 37
Tytuł:
THE METHODS OF FORECASTING OF CHANGES OF MUNICIPAL WASTE PRODUCTION IN CASE OF CITIES
Autorzy:
Cheba, Katarzyna
Powiązania:
https://bibliotekanauki.pl/articles/655807.pdf
Data publikacji:
2014
Wydawca:
Uniwersytet Łódzki. Wydawnictwo Uniwersytetu Łódzkiego
Tematy:
forecasting
municipal waste
regression models
cities
Opis:
Waste management is currently one of the most important problems of the functioning of densely populated areas, important in the case of cities. The main problem of waste management is to break a simple correlation between economic growth and the increase in the amount of waste. Forecasting of amount of municipal waste generation on the basis of previously applied methods in the situation of large changes in socio-economic environment turns out to be inaccurate approach. In the literature a wide variety of geographically diverse factors are proposed for this purpose. This paper presents the results of modeling and forecasting of municipal waste generation changes in cities.  In this study, the impact of the various socio-economic factors for the municipal waste production was tested.
Źródło:
Acta Universitatis Lodziensis. Folia Oeconomica; 2014, 3, 302
0208-6018
2353-7663
Pojawia się w:
Acta Universitatis Lodziensis. Folia Oeconomica
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Bayesian Variations on the Frisch and Waugh Theme
Autorzy:
Osiewalski, Jacek
Powiązania:
https://bibliotekanauki.pl/articles/483315.pdf
Data publikacji:
2011
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
Bayesian inference
regression models
SURE models
VAR processes
data transformations
Opis:
The paper is devoted to discussing consequences of the so-called Frisch-Waugh Theorem to posterior inference and Bayesian model comparison. We adopt a generalised normal linear regression framework and weaken its assumptions in order to cover non-normal, jointly elliptical sampling distributions, autoregressive specifications, additional nuisance parameters and multi-equation SURE or VAR models. The main result is that inference based on the original full Bayesian model can be obtained using transformed data and reduced parameter spaces, provided the prior density for scale or precision parameters is appropriately modified.
Źródło:
Central European Journal of Economic Modelling and Econometrics; 2011, 3, 1; 39-47
2080-0886
2080-119X
Pojawia się w:
Central European Journal of Economic Modelling and Econometrics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Some remarks on permutation type tests in linear models
Autorzy:
Husková, Marie
Picek, Jan
Powiązania:
https://bibliotekanauki.pl/articles/729768.pdf
Data publikacji:
2004
Wydawca:
Uniwersytet Zielonogórski. Wydział Matematyki, Informatyki i Ekonometrii
Tematy:
hypotheses testing
linear regression models
L₁- and L₂ - procedures
Opis:
The paper discusses applications of permutation arguments in testing problems in linear models. Particular attention will be paid to the application in L₁-test procedures. Theoretical results will beaccompanied by a simulation study.
Źródło:
Discussiones Mathematicae Probability and Statistics; 2004, 24, 2; 151-181
1509-9423
Pojawia się w:
Discussiones Mathematicae Probability and Statistics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A Statistical Approach To Prediction Of The CMM Drift Behaviour Using A Calibrated Mechanical Artefact
Autorzy:
Cuesta, E.
Alvarez, B.
Sanchez-Lasheras, F.
Gonzalez-Madruga, D.
Powiązania:
https://bibliotekanauki.pl/articles/221090.pdf
Data publikacji:
2015
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
multivariate regression models
coordinate measuring machine
drift behaviour
calibration
Opis:
This paper presents a multivariate regression predictive model of drift on the Coordinate Measuring Machine (CMM) behaviour. Evaluation tests on a CMM with a multi-step gauge were carried out following an extended version of an ISO evaluation procedure with a periodicity of at least once a week and during more than five months. This test procedure consists in measuring the gauge for several range volumes, spatial locations, distances and repetitions. The procedure, environment conditions and even the gauge have been kept invariables, so a massive measurement dataset was collected over time under high repeatability conditions. A multivariate regression analysis has revealed the main parameters that could affect the CMM behaviour, and then detected a trend on the CMM performance drift. A performance model that considers both the size of the measured dimension and the elapsed time since the last CMM calibration has been developed. This model can predict the CMM performance and measurement reliability over time and also can estimate an optimized period between calibrations for a specific measurement length or accuracy level.
Źródło:
Metrology and Measurement Systems; 2015, 22, 3; 417-428
0860-8229
Pojawia się w:
Metrology and Measurement Systems
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Switching regression models with non-normal errors
Modele regresji przełącznikowej ze składnikami losowymi o rozkładach rożnych od normalnego
Autorzy:
Pruska, Krystyna
Powiązania:
https://bibliotekanauki.pl/articles/904609.pdf
Data publikacji:
1997
Wydawca:
Uniwersytet Łódzki. Wydawnictwo Uniwersytetu Łódzkiego
Tematy:
switching regression models
maximum likelihood method
pseudo maximum likelihood method
Opis:
In this paper two forms of switching regression models with non-normal errors are considered. The pseudo maximum likelihood method is proposed for the estimation of their parameters. Monte Carlo experiments results are presented for a special switching regression model, too. In this research there are compared distributions of parameters estimators for different distributions of errors. The error distributions are as follows: normal, Student’s or Laplace’s. The maximum likelihood method (for the normal errors) is applied to the estimation. In most of the cases the estimators distributions do not differ significantly.
Źródło:
Acta Universitatis Lodziensis. Folia Oeconomica; 1997, 141
0208-6018
2353-7663
Pojawia się w:
Acta Universitatis Lodziensis. Folia Oeconomica
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Implementing GIS and linear regression models to investigate partial building failures
Autorzy:
Merza, Alaa Nuri
Raheem, Aram Mohammed
Naser, Ibrahim Jalal
Ibrahim, Mohammed Omar
Omar, Najat Qader
Powiązania:
https://bibliotekanauki.pl/articles/36072623.pdf
Data publikacji:
2023
Wydawca:
Szkoła Główna Gospodarstwa Wiejskiego w Warszawie. Wydawnictwo Szkoły Głównej Gospodarstwa Wiejskiego w Warszawie
Tematy:
GIS
IDW technique
crack identification
linear single
multi-regression models
Opis:
One of the most dangerous field problems in the civil engineering discipline is the suddenly developed cracks in the building, which could be caused by the swelling of the subsurface soil. Thus, this work has focused on employing a procedure in the geographic information system known as the inverse distance weighted (IDW) technique, to analyze the extent of cracks in a residential complex in the city of Kirkuk in Iraq using the physical and chemical soil data for seven boreholes from the field of the study. Physical soil parameters such as liquid limit (LL), gravel, sand, silt and clay percentages were characterized first, followed by chemical properties such as gypsum content (GYP), total suspended solids (TSS), potential of hydrogen (pH), and organic content (ORG). Furthermore, statistical studies such as plasticity index (PI) and soil characteristics association, linear single, and various linear multi-regression models were used. The data analysis shows that there are significantly positive and negative relationships between PI as a swelling indicator and the physical and chemical soil properties, although weak to moderate correlations were observed between PI and these variables. The PI values were accurately predicted by the proposed linear multi-regression models of the physical and integrated physical and chemical soil characteristics, with multiple R values of 0.92 for both models. As a result, the suggested statistical models can provide complete geographic and mechanical explanations for the crack sources in the investigated residential complex.
Źródło:
Scientific Review Engineering and Environmental Sciences; 2023, 32, 4; 338-356
1732-9353
Pojawia się w:
Scientific Review Engineering and Environmental Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
The use of operational cash flow in the estimation of accrual-based earnings management
Autorzy:
Comporek, Michał
Powiązania:
https://bibliotekanauki.pl/articles/947634.pdf
Data publikacji:
2019
Wydawca:
Wydawnictwo Uniwersytetu Ekonomicznego we Wrocławiu
Tematy:
accrual-based earnings management
operational cash flow
net income
regression models
Opis:
One of the most important analytical spheres enabling the diagnostic estimation of intentional changes in a company’s financial result is the area of accrual adjustments of net profit, separated in the cash flow statement prepared using the indirect method. The special cognitive value of accrual differences can be seen when the structure of total accruals is separated by those adjustments that are not directly related to the real activity of the enterprise, and are the result of subjective accounting choices. The main objective of the article is to present the selected econometric models used for examining accrual-based earnings management phenomenon in Poland. The analysis includes following regression models, namely: the Jones model, the Kasznik model, the Dechow-Dichev model and the McNichols model. The empirical studies were conducted among listed companies qualified for the Warsaw Stock Exchange indices: WIG-20 and mWIG-40, whose shares were traded for at least ten years in 1998-2017.
Źródło:
Financial Sciences. Nauki o Finansach; 2019, 24, 2; 46-60
2080-5993
2449-9811
Pojawia się w:
Financial Sciences. Nauki o Finansach
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
An Evaluation of Some Machine Learning Algorithms as Tools for Predicting Soil Characteristics Based on Their Spectral Response in the Vis‑NIR Range
Autorzy:
Gruszczyński, Stanisław
Powiązania:
https://bibliotekanauki.pl/articles/1838007.pdf
Data publikacji:
2021
Wydawca:
Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie. Wydawnictwo AGH
Tematy:
machine learning
soil properties
near infrared spectral response
stacked regression models
Opis:
Using the Land Use and Coverage Frame Survey (LUCAS) database of European soil surface layer properties, statistical and machine learning predictive models for several key soil characteristics (clay content, pH in CaCl2 , concentration of organic carbon, calcium carbonates and nitrogen and exchange cations capacity) were compared on the basis of processing their spectral responses in the visible (Vis) and near infrared (NIR) parts. Standard methods of relationship modeling were used: stepwise regression, partial least squares regression and linear regression with input data obtained from principal components analysis. Using the inputs extracted by statistical algorithms various machine learning algorithms were used in the modeling. The usefulness of the models was analyzed by comparison with the values of the determination coefficients, the root mean square error and the distribution of residual values. The mean square error of estimation in the cross validation procedure for the stack mod el using the multilayer perceptron and the distributed random forest were as follows: for clay content – ca. 4.5%; for pH – ca. 0.35; for SOC – ca. 7.5 g/kg (0.75% by weight); for CaCO3 content – ca. 19 g/kg; for N content – ca. 0.50 g/kg; and for CEC – ca. 3.5 cmol(+)/kg.
Źródło:
Geomatics and Environmental Engineering; 2021, 15, 1; 63-95
1898-1135
Pojawia się w:
Geomatics and Environmental Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Improving Diesel Engine Reliability Using an Optimal Prognostic Model to Predict Diesel Engine Emissions and Performance Using Pure Diesel and Hydrogenated Vegetable Oil
Autorzy:
Žvirblis, Tadas
Hunicz, Jacek
Matijošius, Jonas
Rimkus, Alfredas
Kilikevičius, Artūras
Gęca, Michał
Powiązania:
https://bibliotekanauki.pl/articles/28328353.pdf
Data publikacji:
2023
Wydawca:
Polska Akademia Nauk. Polskie Naukowo-Techniczne Towarzystwo Eksploatacyjne PAN
Tematy:
engine’s reliability
statistical regression analysis
linear regression models
ANCOVA
MAPE
hydrotreated vegetable oil
Opis:
The reliability of internal combustion engines becomes an important aspect when traditional fuels with biofuels. Therefore, the development of prognostic models becomes very important for evaluating and predicting the replacement of traditional fuels with biofuels in internal combustion engines. The models have been made to model AVL 5402 engine emission, vibration, and sound pressure parameters using a three-stage statistical regression models. The fifteen parameters might be accurately predicted by a single statistic presented here. Both fuel type (diesel fuel and HVO) and engine parameters that can be adjusted were considered, since this analysis followed the symmetry of the methods. The data analysis process included three distinct steps and symmetric statistical regression testing was performed. The algorithm examined the effectiveness of various engine settings. Finally, the optimal fixed engine parameter and the optimal statistic were used to construct an ANCOVA model. The ANCOVA model improved the accuracy of prediction for all fifteen missing parameters.
Źródło:
Eksploatacja i Niezawodność; 2023, 25, 4; art. no. 174358
1507-2711
Pojawia się w:
Eksploatacja i Niezawodność
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Time series analysis in environmental epidemiology: challenges and considerations
Autorzy:
Gudziunaite, Sandra
Shabani, Zana
Weitensfelder, Lisbeth
Moshammer, Hanns
Powiązania:
https://bibliotekanauki.pl/articles/23364734.pdf
Data publikacji:
2023-12-15
Wydawca:
Instytut Medycyny Pracy im. prof. dra Jerzego Nofera w Łodzi
Tematy:
statistical methods
regression models
environmental epidemiology
short-term effects
time series analyses
confounder control
Opis:
In environmental epidemiology, time series analyses represent a widely used statistical tool. However, though being commonly used, there is soften confusion regarding the specific requirements, such as which link function might be most appropriate, when or how to control for seasonality or how to account for lags. The present overview draws from experiences in other disciplines and discusses the proper execution of time series analyses based on considerations that are relevant in environmental epidemiology. Time series analysis in environmental epidemiology focuses on acute events caused by short-term changes in exposure. These exposures should be fairly wide-spread affecting a large number of persons, usually all inhabitants of a political entity. Pollutants in air or drinking water as well as meteorological factors serve as typical examples. Despite the many time series analyses performed world-wide, some health effects that would lend themselves to that approach are still under-explored. This would include also some neurological and psychiatric endpoints.
Źródło:
International Journal of Occupational Medicine and Environmental Health; 2023, 36, 6; 704-716
1232-1087
1896-494X
Pojawia się w:
International Journal of Occupational Medicine and Environmental Health
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
REGIONAL GROWTH DETERMINANTS IN UKRAINE: PANEL DATA ESTIMATES
CZYNNIKI WZROSTU REGIONALNEGO NA UKRAINIE: OSZACOWANIE NA PODSTAWIE DANYCH PANELOWYCH
Autorzy:
Shevchuk, Victor
Powiązania:
https://bibliotekanauki.pl/articles/654657.pdf
Data publikacji:
2014
Wydawca:
Uniwersytet Łódzki. Wydawnictwo Uniwersytetu Łódzkiego
Tematy:
Ukraina
wzrost regionalny
warunkowa konwergencja
modele regresji.
Ukraine
regional growth
conditional convergence
regression models.
Opis:
Wykorzystując zbilansowany zbiór danych panelowych 26 regionów Ukrainy w okresie lat 2002-2012, oszacowano czynniki regionalnego wzrostu regionalnego w ujęciu realnym. Zastosowano estymatory z efektami stałymi (fixed effects) oraz Arellano-Bonda. Spośród standardowych czynników wzrostu gospodarczego, stwierdzono pozytywne oddziaływanie inwestycji w zasoby kapitału fizycznego oraz wzrostu liczby ludności. Wyższa inflacja jest negatywnym czynnikiem wzrostu gospodarczego, w tym jak deprecjacja realnego kursu walutowego ma pozytywne oddziaływanie na ten wskaźnik (oba te rezultaty są standardowymi relacjami makroekonomicznymi). Pozytywny wpływ poziomu eksportu otrzymano wyłącznie dla regionów Wschodniej i Południowej Ukrainy z wyższym poziomem produktu regionalnego (dochodu) na mieszkańca. Według podejścia D’Costa et al. (2013), zbadano zależność otrzymanych wyników od luki dochodu pomiędzy poszczególnymi regionami a regionem granicznym – z najwyższym poziomem dochodu, tzn. stolicznym miastem Kijowem. Podobnie do innych badan (Crespo Cuaresma et al. 2009; Ledyaeva, Inden 2008), otrzymano świadczenia na korzyść konwergencji warunkowej jak to uwyraźnia negatywna relacja między początkowym poziomem produktu na mieszkańca a stopa wzrostu dochodu w następnych latach. Jak to sugerują odpowiednie współczynniki regresyjne, konwergencja warunkowa jest mocniejszą wśród regionów z wyższym poziomem dochodu niż wśród regionów z niższym poziomem dochodu. Rezultaty są odporne na wybór estymatorów oraz specyfikacji modelu regresyjnego.
In this paper, determinants of real regional per capita growth were estimated using a balanced panel data set consisting of 26 Ukrainian regions for the period from 2002 to 2012. The Arellano-Bond dynamic panel data estimation technique was applied. Among the traditional factors of economic growth, positive effects of investments in physical capital and population growth (for the high-income regions only) were found. Higher inflation and a larger share of rural population are negative regional growth factors, while the depreciation of the real exchange rate and increase in the export of goods has an opposite pro-growth impact. As suggested by the lagged level of the output coefficients, conditional convergence is faster among the high-income regions. The results are robust to the choice of estimators and regression model specifications.
Źródło:
Acta Universitatis Lodziensis. Folia Oeconomica; 2014, 5, 307
0208-6018
2353-7663
Pojawia się w:
Acta Universitatis Lodziensis. Folia Oeconomica
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Fostering Czech firms innovation performance through efficient cooperation
Autorzy:
Prokop, Viktor
Kotkova Striteska, Michaela
Stejskal, Jan
Powiązania:
https://bibliotekanauki.pl/articles/19233701.pdf
Data publikacji:
2021
Wydawca:
Instytut Badań Gospodarczych
Tematy:
public support of innovation
cooperation
national and European subsidies
manufacturing
R&D
regression models
Czech Republic
Opis:
Research background: The business climate development and the stage of innovation systems' transformation are very similar in many Central and Eastern European countries, making it necessary to study these specific economies. These economies are at a different level of transformation, and their governments are trying to support the development of a knowledge-based economy, the creation of innovation systems, and collaboration among different types of entities. These governments need feedback in the form of research into the impacts of public funding on innovation activities through the influence of basic research and cooperation-based resources in individual countries. Purpose of the article: This paper focuses on the examination of (i) the influence of national and European subsidies on innovation performance in manufacturing firms in the Czech Republic and (ii) impacts of knowledge- and cooperation-based resources on innovation activities in Czech manufacturing. Methods: The latest available data from the Community Innovation Survey was used for analyses realized by different regression models. The proposed research models were gradually created to verify the influence of pro-innovation factors (expenditures on in-house and external R&D and on the acquisition of external tangible and intangible sources, cooperation with different partners and innovation) and public (national and/or European) funding of firms' innovation performance within the Czech manufacturing industry. Findings and value added: The results have showed that there is a need to focus on direct and indirect effects of selected innovation determinants; we have also identified the crucial role of cooperation (specifically with government, public, or private research institutes) as a mediating variable within innovation processes. The results have also evidenced that public funding affects the efficiency of knowledge- and cooperation-based resources and amplifies the impact on firms' innovation performance differently. Whereas subsidies from national budgets do not significantly influence the innovation performance of Czech manufacturing firms, European subsidies, on the other hand, significantly increase firms' innovation performance. A long-term contribution of this paper is the significant completion of the theory of policy implications that may be applicable in a broad international context beyond the borders of the Czech Republic. This study significantly contributes to the ongoing discussion about (i) the significance of public financial subsidies from both national and European funds and (ii) the effects of cooperation and R&D on firms? innovation performance within "catching-up" in Central and Eastern Europe. 
Źródło:
Oeconomia Copernicana; 2021, 12, 3; 671-700
2083-1277
Pojawia się w:
Oeconomia Copernicana
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Fuzzy c-regression models in bacterial population dynamics modelling
Autorzy:
Owczarek, A.
Momot, M.
Sobierska, E.
Powiązania:
https://bibliotekanauki.pl/articles/333140.pdf
Data publikacji:
2003
Wydawca:
Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:
rozmyte modele c-regresji
bakteryjne modelowanie wzrostu
odcinkowa funkcja ciągła
fuzzy c-regression models
bacterial growth modelling
piecewise continuous functions
Opis:
The paper describes application of the fuzzy c-regression models algorithm in bacterial population dynamics modelling. Such a well-known algorithm, which provides simultaneous estimates of the parameters of c-regression models, together with a fuzzy partitioning of data, was used to determine bacterial growth curve given by the piecewise continuous function. The real as well as artificial data were used and promising results were obtained even for data with significant errors resulting from the measurement inaccuracy.
Źródło:
Journal of Medical Informatics & Technologies; 2003, 5; MI75-82
1642-6037
Pojawia się w:
Journal of Medical Informatics & Technologies
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Land clayey deposits compressibility investigation using principal component analysis and multiple regression tools
Autorzy:
Berrah, Yacine
Chegrouche, Aymen
Brahmi, Serhane
Boumezbeur, Abderrahmane
Powiązania:
https://bibliotekanauki.pl/articles/2201674.pdf
Data publikacji:
2022
Wydawca:
Uniwersytet Rolniczy im. Hugona Kołłątaja w Krakowie
Tematy:
compressibility index
geotechnical parameters
principal component analysis
PCA
multiple regression models
indeks ściśliwości
parametry geotechniczne
analiza głównych składowych
regresja wielokrotna
Opis:
The settlement and compressibility magnitude of the major clayey and marly sediments in Tebessa area (N-E of Algeria) depends on several geotechnical parameters such as compression Cc and recompression Cs indices. The aim of this study was to investigate the parameters related to soil compressibility through tools of statistical analysis, which save time in comparison to multiply repeated laboratory tests. The study also adopted the principal component analysis (PCA) method to eliminate a number of uncorrelated variables that have no influence on the compressibility magnitude, or their impact is insignificant. The highest mean correlation coefficients were obtained for different contributing parameters. Multiple regression analysis has been performed to obtain the best fit model of the output Cc parameter taking into account the best correlation by adding parameters as regressors to reach the highest coefficient of regression R2 . The final obtained model of the present case study gives the best fit model with R2 of 0.92 which is a better value compared to different published models in the literature (R2 of 0.7 as maximum). The chosen input parameters using PCA combined with multiple regression analysis allow identifying the most important input parameters that noticeably affect the soil compression index, and provide with the best model for estimating the Cc index.
Źródło:
Geomatics, Landmanagement and Landscape; 2022, 4; 95--107
2300-1496
Pojawia się w:
Geomatics, Landmanagement and Landscape
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Prediction of monthly averages of air pollutant concentrations for selected areas in Mazovian Voivodeship
Predykcja średniomiesięcznych stężeń zanieczyszczeń powietrza dla wybranych obszarów województwa mazowieckiego
Autorzy:
Hoffman, S.
Filak, M.
Powiązania:
https://bibliotekanauki.pl/articles/297072.pdf
Data publikacji:
2018
Wydawca:
Politechnika Częstochowska. Wydawnictwo Politechniki Częstochowskiej
Tematy:
air pollution
air monitoring
pollutant concentrations
monthly concentrations
multivariate regression models
approximation error
zanieczyszczenia powietrza
monitoring powietrza
stężenia zanieczyszczeń
stężenia średniomiesięczne
modele regresji wielowymiarowej
błąd aproksymacji
Opis:
The study was carried out using long-term data, recorded at two air monitoring stations in Masovian Voivodeship. Hourly time series, obtained from the monitoring system, were averaged in calendar months to get monthly time series. The data sets, containing time series of monthly mean values from two different monitoring sites, were subjected to multivariate regression analysis. Models of multidimensional linear regression were built for the both sets of data. The obtained models describe statistical dependencies between concentrations of specified air pollutants and concentrations of other pollutants and meteorological parameters, recorded at the same monitoring station. The achieved regression equations were used to predict long-term courses of monthly concentrations. For visualization of prediction accuracy, the charts containing time series of actual and predicted monthly concentrations were prepared. The approximation precision was estimated by calculating modelling errors for each regression model. Three different measures of approximation error were applied: mean absolute error (MAE), root mean square error (RMSE), and Pearson correlation coefficient (r).
Badania przeprowadzono, wykorzystując wieloletnie dane pomiarowe zarejestrowane na dwóch stacjach monitoringu powietrza w województwie mazowieckim. 1-godzinne serie czasowe uśredniono w okresach miesięcznych, uzyskując średniomiesięczne serie czasowe. Zbiory danych zawierających serie czasowe wartości średniomiesięcznych poddano analizie regresji wielowymiarowej. W obu zbiorach szukano modeli wielowymiarowej regresji liniowej, opisujących statystyczną zależność stężeń poszczególnych zanieczyszczeń powietrza od stężeń pozostałych zanieczyszczeń i od parametrów meteorologicznych. Otrzymane równania regresji wykorzystano do predykcji średniomiesięcznych stężeń zanieczyszczeń powietrza. Sporządzono wykresy zawierające serie czasowe rzeczywistych i przewidywanych stężeń średniomiesięcznych, które pozwoliły na wizualizację dokładności predykcji. Oszacowano również dokładność aproksymacji, obliczając błędy modelowania dla każdego z modeli regresyjnych. Zastosowano trzy różne miary błędu aproksymacji, obliczając dla modeli regresyjnych średni błąd bezwzględny (MAE), pierwiastek z błędu średniokwadratowego (RMSE), współczynnik korelacji Pearsona (r).
Źródło:
Inżynieria i Ochrona Środowiska; 2018, 21, 4; 321-333
1505-3695
2391-7253
Pojawia się w:
Inżynieria i Ochrona Środowiska
Dostawca treści:
Biblioteka Nauki
Artykuł
Wyświetlanie 1-15 z 37

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