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1

Evaluation of the performance of data-driven approaches for filling monthly precipitation gaps in a semi-arid climate conditions

Katipoğlu Okan Mert

Acta Geophysica

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2023

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Vol. 71, no. 5

2265--2285

EN

Missing data cause problems in meteorological, hydrological, and climate analysis. The observation data should be complete and cover long periods to make the research more accurate and reliable. Artificial intelligence techniques have attracted interest for completing incomplete meteorological data in recent years. In this study the abilities of machine learning models, artificial neural networks, the nonlinear autoregressive with exogenous input (NARX) model, support vector regression, Gaussian processes regression, boosted tree, bagged tree (BAT), and linear regression to fill in missing precipitation data were investigated. In developing the machine learning model, 70% of the dataset was used for training, 15% for testing, and 15% for validation. The Bayburt, Tercan, and Zara precipitation stations, which are closest to the Erzincan station and have the highest correlation coefficients, were used to fill the data gaps. The accuracy of the constructed models was tested using various statistical criteria, such as root-mean-square error (RMSE), mean absolute error (MAE), Nash–Sutcliffe model efficiency coefficient (NSE), and determination coefficient (R2) and graphical approaches such as scattering, box plots, violin plots, and Taylor diagrams. Based on the comparison of model results, it was concluded that the BAT model with R2: 0.79 and NSE: 0.79 and error (RMSE: 11.42, and MAE: 7.93) was the most successful in the completion of missing monthly precipitation data. The contribution of this research is assist in the choice of the best and most accurate method for estimating precipitation data in semi-arid regions like Erzincan.

2

Pattern recovery and signal denoising by SLOPE when the design matrix is orthogonal

Skalski Tomasz, Kołodziejek Bartosz, Graczyk Piotr, Wilczyński Maciej

Probability and Mathematical Statistics

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2022

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Vol. 42, Fasc. 2

283--302

EN

Sorted ℓ1 Penalized Estimator (SLOPE) is a relatively new convex regularization method for fitting high-dimensional regression models. SLOPE allows the reduction of the model dimension by shrinking some estimates of the regression coefficients completely to zero or by equating the absolute values of some nonzero estimates of these coefficients. This allows one to identify situations where some of true regression coefficients are equal. In this article we will introduce the SLOPE pattern, i.e., the set of relations between the true regression coefficients, which can be identified by SLOPE. We will also present new results on the strong consistency of SLOPE estimators and on the strong consistency of pattern recovery by SLOPE when the design matrix is orthogonal and illustrate advantages of the SLOPE clustering in the context of high frequency signal denoising.

3

Regresja i niepewność linii prostej dla pomiarów obu zmiennych x i y ze wszystkimi korelacjam

Puchalski Jacek, Warsza Zygmunt Lech

Pomiary Automatyka Robotyka

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2022

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R. 26, nr 2

47--58

PL

Praca kontynuuje cykl publikacji o szacowaniu metodą regresji liniowej parametrów równania i granic pasma niepewności linii prostej y = ax + b dopasowanej do wyników pomiarów obu współrzędnych punktów badanych. Rozpatrzono przypadek ogólny, gdy współrzędne te mają różne niepewności i występują wszystkie możliwe autokorelacje i korelacje wzajemne. Zastosowano opis równaniami macierzowymi. Wyniki pomiarów współrzędnych przedstawiono jako elementy wektorów w X i Y. Propagację niepewności opisano macierzą kowariancji UZ o czterech macierzach składowych, tj. UX i UY - dla niepewności i autokorelacji zmiennych X i Y oraz UXY i jej transpozycja UTXY - dla korelacji wzajemnych. Podano równanie linii prostej i granice jej pasma niepewności. Otrzymane je dla funkcji parametrów a i b spełniającej tzw. kryterium totalne WTLS, tj. minimum sumy kwadratów odległości punktów od prostej ważonych przez odwrotności niepewności współrzędnych. Przy nieskorelowaniu współrzędnych różnych punktów stosuje się uproszczone kryterium WLS. Kierunki rzutowania punktów wnikają z minimalizacji funkcji opisującej kryterium. W przypadku ogólnym istnieje tylko rozwiązanie numeryczne. Zilustrowano to przykładem. Parametry a i b linii prostej wyznaczono numerycznie z powiększonych fragmentów wykresu funkcji kryterialnej wokół jej minimum. Podano też warunki wymagane dla niepewności i korelacji współrzędnych punktów, które umożliwiają uzyskanie rozwiązania analitycznego i jego przykład.

EN

The work continues the series of publications on the estimation of the parameters of the equation and the limits of the uncertainty band of the straight-line y = ax + b fitted to the measurement results of both coordinates of the tested points with the use of the linear regression method. A general case was considered when these coordinates have different uncertainties and there are all possible autocorrelations and cross-correlations. Description of matrix equations was used. The results of the coordinate measurements are presented as elements of the X and Y vectors. The propagation of their uncertainty was described by the UZ covariance matrix with four component matrices, i.e., UX and UY - for the uncertainties and autocorrelations of X and of Y, and UXY and its transposition UTXY - for the cross-correlations. The equation of a straight line and of the borders of its uncertainty band are given. Obtained them for the function of parameters a and b satisfying the so-called total criterion WTLS, i.e., the minimum sum of squared distances of points from the straight line weighted by the reciprocal of the coordinate uncertainty. When the coordinates of different points are not correlated, the simplified criterion WLS is used. The directions of projecting the points result from the minimization of the function describing the criterion. In the general case, there is only a numerical solution. This is illustrated by an example, in which the parameters a and b of the straight line were determined numerically from the enlarged fragments of the graph of the criterion function around its minimum. The conditions for the uncertainty and correlation of coordinates of points required to obtain an analytical solution and its example are also given.

4

An accurate model of LED luminaire using measurement results for estimation of electrical parameters based on the multivariable regression method

Sikora Roman, Markiewicz Przemysław, Rózga Paweł

Metrology and Measurement Systems

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2022

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Vol. 29, nr 2

251--269

EN

Light sources and luminaires made in the LED technology are nowadays widely used in industry and at home. The use of these devices affects the operation of the power grid and energy efficiency. To estimate this impact, it is important to know the electrical parameters of light sources and luminaires, especially with the possibility of dimming. The article presents the results of measurements of electrical parameters as well as luminous flux of dimmable LED luminaires as a function of dimming and RMS supply voltage. On the basis of the performed measurements, a model of LED luminaire was developed for prediction of electrical parameters at set dimming values and RMS values of the supply voltage. The developed model of LED luminaire has 2 inputs and 26 outputs. This model is made based on 26 single models of electrical parameters, whose input signals are supply and control voltages. The linear regression method was used to develop the models. An example of the application of the developed model for the prediction of electrical parameters simulating the operation of an LED luminaire in an environment most similar to real working conditions is also presented.

5

Uogólniona metoda najmniejszych kwadratów

Puchalski Jacek

Metrologia i Probiernictwo : biuletyn Głównego Urzędu Miar

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2022

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nr 1 (28)

9--16

PL

Artykuł przedstawia uogólnione podejście dla dobrze znanej metody najmniejszych kwadratów stosowanej w praktyce metrologicznej. Wyznaczone niepewności punktów pomiarowych i korelacje między mierzonymi zmiennymi tworzą symetryczną macierz kowariancji, której odwrotność mnożona jest lewostronnie i prawostronnie przez wektory błędów obu zmiennych losowych i stanowi funkcję kryterialną celu. Aby uzyskać maksymalną wartość funkcji największej wiarygodności i rozwiązać złożony problemu minimalizacji funkcji kryterialnej, zaprezentowano oryginalny sposób wyznaczenia funkcji kryterialnej do postaci jednoargumentowej zależności obliczanej numerycznie, w której jedyną zmienną jest poszukiwany współczynnik kierunkowy prostej regresji. Artykuł zawiera podstawowe informacje o tego typu regresji liniowej, dla której najlepiej dopasowana prosta minimalizuje funkcję celu. Na przykładzie obliczeniowym pokazana jest pełna procedura dopasowania numerycznego prostej do danego zestawu punktów pomiarowych o zadanych niepewnościach i współczynnikach korelacji tworzących macierz kowariancji.

EN

The paper presents a generalized approach for the well-known least squares method used in metrological practice. In order to solve the complex problem of minimizing the objective function to obtain the maximum value of the likelihood function, the original way of determining this function in the form of a unary relationship calculated numerically was presented. The article presents borderline cases with analytical solutions. The computational example shows the full procedure of numerical adjustment of a straight line to a given set of measurement points with given uncertainties and correlation coefficients forming the covariance matrix.

6

Assessment of the benefits of implementing the EMS system on the example of a container glass industry

Dec Przemysław, Skorek-Osikowska Anna

Journal of Power Technologies

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2022

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Vol. 102, nr 4

160--174

EN

The paper describes the glass manufacturing process, the process areas and their energy intensity. The implementation of an energy management system, its operation and participation in the decision-making chain as well as benefits from implementation are also described. The use of regression as a numerical technique for determining energy consumption is presented with reference to the historical experience of the glassworks and its developed trends on the example of gas consumption in the melting process in the glass furnace. The paper compared the deviation of actual energy consumption in the glass melting process to that calculated from linear regression variables for data before and after the implementation of the Energy management system. The study confirmed the sensibility of implementing the described managing system. Constant observation and response to factors affecting the running process allows for its stabilization and optimization.

7

The Interaction of Chlorophyll-a and Total Suspended Matter along the Western Semarang Bay, Indonesia, Based on Measurement and Retrieval of Sentinel 3

Maslukah Lilik, Ismunarti Dwi Haryo, Widada Sugeng, Sandi Nur Fikri, Prayitno Hanif Budi

Journal of Ecological Engineering

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2022

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Vol. 23, nr 10

191--201

EN

The Kendal Regency area is one of the areas on the northern coast of Central Java that has been experiencing rapid industrial development. The high human activity in this area will impact the quality of water in these surrounding areas and affect the fertility of the waters. The concentrations of chlorophyll-a (Chl-a) and total suspended matter (TSM) are major water quality parameters that can be retrieved using remotely sensed data. The retrieval satellite of the 3 OLCI chosen in this study has a 300 m spatial resolution. This study aimed to see the distribution and effect of total suspended matter (TSM) on chlorophyll-a based on measurement and retrieval of Sentinel 3 imagery using the linear regression method. The results show the chlorophyll-a distribution and the value from retrieval satellite are higher and occur over larger surface area compared to chlorophyll-a measurements. The linear regression model of chlorophyll-a by retrieval satellite imagery and measurement is y = 0.65x + 4.65 with R2 = 0.54. The presence of high amounts of suspended solids in the waters causes disturbances in the reflectance values, which are recorded by the retrieval of satellite. The model regression chlorophyll-a with TSM accuracy from retrieval satellite results in the equation y = -0.0416x + 5.14 (R2 = 0.45, p = 0.05, n = 13). The determination (R2) coefficient value is 0.445, which means that suspended solids have a 44.5% effect on chlorophyll-a and 55.5% is influenced by other factors and not examined in this study. The results show that TSM has an influence on the accuracy of chlorophyll-a and retrieval satellite recording can be disrupted if waters have high turbidity.

8

Econometric models - a method for examining factors of implementation of public-private partnership projects in selected European countries

Rogowski Andrzej, Zagożdżon Beata

Journal of civil engineering and transport

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2022

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Vol. 4, No. 3

25--55

EN

Modern science is based on the study of economic phenomena and tries to quantify them in a measurable way. Econometric models are used for this purpose. The objectof this research was to develop econometric models that show the strength of the influence of various factors on the implementation of public-private partnership (PPP) projects in the area of transport infrastructure in France, GB, Germany, the Netherlands and Belgium. The models express the dependence of the value and number of PPP contracts on the value of measurable PPP success factors. Projects with a value of at least €40 million were included. A linear model and seven models transformable to linear were used. Four groups of factors were considered as explanatory variables. Fourteen indicators were obtained. Principal components determined based on covariance and correlation matrices were also used. The best models for the number of PPP contracts are linear and hyperbolic I models. For the value of contracts - linear and hyperbolic I and logarithmic models. The best models were indicated taking into account the type of explanatory variables and regardless of the type of explanatory variables. Nine criteria were used to assess the quality of the models. Factors having a significant impact on the value and number of PPP models were identified from the best models. Factors having no significant influence were also indicated.

PL

Współczesna nauka opiera się na badaniu zjawisk ekonomicznych i stara się je kwantyfikować w sposób wymierny. Do tego celu wykorzystuje się modele ekonometryczne. Przedmiotem badań było opracowanie modeli ekonometrycznych, które pokazują siłę wpływu różnych czynników na realizację projektów partnerstwa publiczno-prywatnego (PPP) w obszarze infrastruktury transportowej w Francji, Wielkiej Brytanii, Niemczech, Holandii i Belgii. Modele te wyrażają zależność wartości i liczby kontraktów PPP od wartości mierzalnych czynników sukcesu PPP. Uwzględniano projekty o wartości co najmniej 40 mln euro. Zastosowano model liniowy oraz siedem modeli przekształcalnych do liniowego. Jako zmienne objaśniające uwzględniono cztery grupy czynników. Uzyskano czternaście wskaźników. Wykorzystano również składowe główne wyznaczane w oparciu o macierze kowariancji i korelacji. Najlepszymi modelami dla liczby umów PPP są modele liniowe i hiperboliczne I. Dla wartości umów - modele liniowe i hiperboliczne I i logarytmiczne. Wskazano modele najlepsze z uwzględnieniem typu zmiennych objaśniających i bez względu na typ zmiennych objaśniających. Do oceny jakości modeli wykorzystano dziewięć kryteriów. Na podstawie modeli najlepszych wskazano czynniki mające istotny wpływ na wartość i liczbę modeli PPP. Wskazano również czynniki nie mające istotnego wpływu.

9

A simulation strategy to determine the mechanical behaviour of cork-rubber composite pads for vibration isolation

Lopes Helena, Silva Susana P., Machado José

Eksploatacja i Niezawodność

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2022

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Vol. 24, no. 1

80--88

EN

The present work aimed to determine the performance of new cork-rubber composites, applying a modelling-based approach. The static and dynamic behaviour under compression of new composite isolation pads was determined using mathematical techniques. Linear regression was used to estimate apparent compression modulus and dynamic stiffness coefficient of compounds samples based on the effect of fillers, cork and other ingredients. Using the results obtained by regression models, finite element analysis (FEA) was applied to determine the behaviour of the same cork-rubber material but considering samples with different dimensions. The majority of the regression models presented R2 values above 90%. Also, a good agreement was found between the results obtained by the presented approach and previous experimental tests. Based on the developed methodology, the compression behaviour of new cork-rubber compounds can be accessed, improving product development stages.

10

Fractal Dimension as Robust Estimate of Low Carbon Steels Hardness

Zając Krzysztof, Płatek Karolina, Wachel Paweł, Łatka Leszek

Advances in Science and Technology. Research Journal

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2022

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Vol. 16, no 5

335--344

EN

Application of computational methods in engineering and science constantly increases, which is also visible in sector of material science, often with promising results. In following paper, authors would like to propose fractal dimension, a mathematical method of quantifying self-similarity and complexity of spatial patterns, as robust method of hardness estimation of low carbon steels. A dataset of microstructure images and corresponding Vickers hardness measurements of S235JR steel under different delivery conditions was created. Then, three different computational methods for evaluation of materials hardness based on microstructure image were tested. In this paper those methods are called: (i) Otsu-based index, (ii) fractal dimension index and (iii) vision transformer index. The results were compared with method used in literature for similar problems. Comparison showed that fractal dimension performs better than other evaluated methods, in terms of median absolute error, which value was equal to 4.12 HV1, which is significantly lower than results achieved by Otsu-based index and vision transformer index, which were 4.49 HV1 and 5.07 HV1 respectively. Those results can be attributed to the relative robustness of fractal dimension index, when compared to other methods. Robust estimation is preferable, due to the high amount of noise in the dataset, which is a consequence of the nature of used material.

11

LNG market and fleet analysis

Stanivuk Tatjana, Mahić Josip, Stazić Ladislav, Perdić-Lukačević Hana

Transport Problems

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2021

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T. 16, z. 4

173--183

EN

This paper is part of larger research on the impact of present and future air emissions from the shipping industry and especially the environmental impact of the rapid spreading of the LNG as a fuel in the industry. Therefore, it was important to gather data related to the LNG market and perform an analysis to gain realistic insight into the market behaviour. This paper analyses the situation and trends of the LNG shipping market over a longer period to predict future developments. Data analysis of the several aspects and patterns of the trade has been performed; the results obtained can enable prediction of the market situation for the future. From the data analysis and predictions of the LNG market, continuous growth in the following years is expected, which linked to an increase of the LNG fleet and number of importing countries. Research has shown that new propulsion alternatives such as MEGI and XDF are appearing on the market as the first choice for new builds, while steam turbines are slowly disappearing. Although market growth is projected from all research parameters, the situation has changed due to the COVID-19 pandemic and its impact on the market. Consequently, growth forecasts will not be realized in 2020.

12

Niepewności pomiarów w metodzie regresji liniowej Część 2. Niepewności prostej dla zmiennej Y o skorelowanych danych

Warsza Zygmunt Lech, Puchalski Jacek

Pomiary Automatyka Robotyka

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2020

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R. 24, nr 4

61--72

PL

Część druga pracy autorów dotyczy oceny dokładności parametrów linii prostej wyznaczanej metodą regresji dla różnych przypadków skorelowania współrzędnych punktów pomiarowych. W pierwszej części pracy rozpatrzono istotę, kryteria i zależności metody regresji oraz wyznaczono równania prostej i jej pasma niepewności dla symulowanych przykładów punktów o nieskorelowanych rzędnych. Nawiązano do zasad oceny dokładności według Przewodnika GUM i uwzględniono niepewność typu B nierozpatrywaną w literaturze o zastosowaniu metod regresji w pomiarach. W tej pracy omawia się wyznaczanie równania prostej regresji i jej pasm niepewności dopasowanych do pomiarów punktów o rzędnych skorelowanych. Ilustrują to przykłady o różnym skorelowaniu oraz niepewnościach bezwzględnych i względnych typów A i B mierzonych wartości zmiennej zależnej Y przy precyzyjnie znanych wartościach zmiennej niezależnej X. Omówiono też wpływ autokorelacji przy stosowaniu sposobu zwiększania dokładności przez wielokrotne powtarzanie pomiarów rzędnej każdego punktu, w tym dla wielokrotnych pomiarów tylko dwu punktów.

EN

This is the continuation of authors’ works on the description of the accuracy of various straight-line cases determined from the results of linear regression measurements. In the first work, the essence, criteria and dependencies of the regression method were examined, as well as simulated examples of determining simple uncertainty bands fitted to measured points with uncorrelated ordinates. The GUM Guide was referred to and the B type uncertainty not discussed yet in the literature about the application of the regression method in measurements was taken into account. This work discusses determining the equation of a simple regression and its uncertainty bands from measuring points with ordinates with autocorrelation. This is illustrated by examples with precisely known abscissa and ordinates with different correlation variants, and absolute and relative uncertainty types A and B. Proposed is the extended method for assessing the accuracy of simple regression takes into account both the correlation of the Y variable data and the impact of type B uncertainty in routine measurements.

13

Niepewności pomiarów w metodzie regresji liniowej. Część 1. Prosta i jej pasma niepewności dla nieskorelowanych danych pomiarowych

Warsza Zygmunt Lech, Puchalski Jacek

Pomiary Automatyka Robotyka

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2020

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R. 24, nr 3

79--91

PL

W serii kilku prac omówi się szacowanie dokładności parametrów linii prostej wyznaczanej metodą regresji liniowej dla różnych przypadków danych pomiarowych. Nawiązując do zaleceń Przewodnika Wyznaczania Niepewności Pomiarów GUM, uwzględnia się pomijaną dotychczas w literaturze niepewność typu B. Pierwsza z tych prac dotyczy pomiarów wartości zmiennej losowej Y dla znanych wartości zmiennej X. Przedstawia się istotę problemu, kryteria metody regresji liniowej i ich zastosowanie dla wartości mierzonych o nieskorelowanych, znanych i nieznanych, w tym jednakowych, niepewnościach typu A. Ilustrują to symulowane przykłady obliczeniowe dla pomiarów punktów o tych samych współrzędnych i różnych wariantach niepewności typu A i typu B. Wyznaczono równania prostej i pasma ich niepewności. Kolejna praca dotyczyć będzie pomiarów punktów o danych skorelowanych. W kolejnej omówi się przypadki wymagające pomiarów obu zmiennych Y i X.

EN

In a series of several papers, the estimation of the accuracy of the parameters of a straight line determined by the linear regression method for various cases of measurement data will be discussed. Referring to the recommendations of the Guide to the Expression of Uncertainty in Measurement, the B-type uncertainty, so far omitted in the literature, is taken into account. The first of these works concerns the measurements of the value of the random variable Y for known values of the variable X. The essence of the problem, the criteria of the linear regression method and their application are presented for measured values with uncorrelated, known and unknown, including the same, type A uncertainties. Simulated calculation examples illustrate the case for the measurements of points with the same coordinates and different variants of type A and type B uncertainty. Line equations and their uncertainty bands were determined. The next work will concern the measurements of points with correlated data. In yet another work, the cases will be discussed cases that require measurements of both Y and X variables.

14

On a characterization of exponential, Pearson and Pareto distributions via covariance and pseudo-covariance

Pawlas Piotr, Szynal Dominik

Demonstratio Mathematica

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2020

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Vol. 53, nr 1

285--291

EN

Properties of linear regression of order statistics and their functions are usually utilized for the characterization of distributions. In this paper, based on such statistics, the concept of Pearson covariance and the pseudo-covariance measure of dependence is used to characterize the exponential, Pearson and Pareto distributions.

15

Anthropometry and Size Groups in the Clothing Industry

Balach Monika, Lesiakowska-Jablonska Marzanna, Frydrych Iwona

Autex Research Journal

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2020

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Vol. 20, no. 1

56--62

EN

It appears that from generation to generation the anthropometric dimensions of the human population are changing. The aim of this paper was to examine the extent of these changes and the need for generating updated measurements for the clothing industry. The clothing industry uses mannequins and avatars to represent the modal group of the population. The industry tends to use three different categories for the human body shape (endomorphic, mesomorphic, and ectomorphic). The clothing industry should focus on specific measurements of the body rather than general categories and create more body shapes to satisfy customer needs. The paper also aimed at showing the problems faced by clothing designers. The traditional way of measuring takes into account only selected dimensions of the human body; this does not reflect the “true” overall body shape. The dimension tables used by the apparel industry are based on the fourth anthropometric photograph taken between 1987 and 1989. These tables are still in the use currently; however, after 30 years they are outdated and should be revised for the young contemporary generation. This study can be used for the development of new dimension tables as well as defining methods aimed at improving the quality of measurements for clothing engineering purposes. This is an important issue, because the National Institute of Anthropometry does not deal with such problems (the measurements are conducted mainly for understanding the human body shape rather than any other application), which means that anthropometric measurements are not ideally suited to applications of clothes fitting.

16

Impact assessment of short-term management measures on travel demand

D'Cruz Jinit J.M., Alex Anu P., Manju V. S., Peter Leema

Archives of Transport

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2020

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Vol. 53, iss. 1

37--52

EN

Travel Demand Management (TDM) can be considered as the most viable option to manage the increasing traffic demand by controlling excessive usage of personalized vehicles. TDM provides expanded options to manage existing travel demand by redistributing the demand rather than increasing the supply. To analyze the impact of TDM measures, the existing travel demand of the area should be identified. In order to get quantitative information on the travel demand and the performance of different alternatives or choices of the available transportation system, travel demand model has to be developed. This concept is more useful in developing countries like India, which have limited resources and increasing demands. Transport related issues such as congestion, low service levels and lack of efficient public transportation compels commuters to shift their travel modes to private transport, resulting in unbalanced modal splits. The present study explores the potential to implement travel demand management measures at Kazhakoottam, an IT business hub cum residential area of Thiruvananthapuram city, a medium sized city in India. Travel demand growth at Kazhakoottam is a matter of concern because the traffic is highly concentrated in this area and facility expansion costs are pretty high. A sequential four-stage travel demand model was developed based on a total of 1416 individual household questionnaire responses using the macro simulation software CUBE. Trip generation models were developed using linear regression and mode split was modelled as multinomial logit model in SPSS. The base year traffic flows were estimated and validated with field data. The developed model was then used for improving the road network conditions by suggesting short-term TDM measures. Three TDM scenarios viz; integrating public transit system with feeder mode, carpooling and reducing the distance of bus stops from zone centroids were analysed. The results indicated an increase in public transit ridership and considerable modal shift from private to public/shared transit.

17

Explicit and implicit description of the factors impact on the NO2 concentration in the traffic corridor

Kamińska Joanna Amelia, Turek Tomasz

Archives of Environmental Protection

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2020

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Vol. 46, no. 1

93--99

EN

High concentrations of nitrogen dioxide in the air, particularly in heavily urbanized areas, have an adverse effect on many aspects of residents’ health. A method is proposed for modelling daily average, minimal and maximal atmospheric NO2 concentrations in a conurbation, using two types of modelling: multiple linear regression (LR) an advanced data mining technique – Random Forest (RF). It was shown that Random Forest technique can be successfully applied to predict daily NO2 concentration based on data from 2015–2017 years and gives better fi t than linear models. The best results were obtained for predicting daily average NO2 values with R2=0.69 and RMSE=7.47 μg/m3. The cost of receiving an explicit, interpretable function is a much worse fit (R2 from 0.32 to 0.57). Verification of models on independent material from the first half of 2018 showed the correctness of the models with the mean average percentage error equal to 16.5% for RF and 28% for LR modelling daily average concentration. The most important factors were wind conditions and traffic flow. In prediction of maximal daily concentration, air temperature and air humidity take on greater importance. Prevailing westerly and south-westerly winds in Wrocław effectively implement the idea of ventilating the city within the studied intersection. Summarizing: when modeling natural phenomena, a compromise should be sought between the accuracy of the model and its interpretability.

PL

Celem pracy jest zbadanie możliwości prognozowania dziennego stężenia NO2 za pomocą metody losowego lasu – RF i porównanie wyników z wielowymiarową regresją liniową (LR) w oparciu o ten sam zestaw danych. Ponadto zbadano wpływ zwiększenia interpretowalności modelu na jego dokładność. W pracy przedstawiono dwie metody modelowania dziennych wartości minimalnych, średnich oraz maksymalnych stężeń NO2 w aglomeracji miejskiej: wielowymiarowa regresja liniowa (LR) oraz losowy las (RF). Wykazano, że metoda Lasu Losowego (Random Forest) może być skutecznie wykorzystywana do przewidywania dziennych wartości stężenia NO2. Największą dokładność otrzymano dla przewidywania średnich wartości dziennych stężenia z R2=0.69 oraz RMSE=7.47 μg/m3. Kosztem otrzymania jawnej postaci funkcji w modeli liniowym (LR) jest znacząco niższa dokładność przewidywania wartości stężenia (R2 od 0.32 do 0.57). Weryfikacja modeli na niezależnym materiale z pierwszej połowy 2018 roku potwierdziła poprawność modeli ze średnim błędem względnym dla średnich wartości dobowych stężeń równym 16.5% dla RF oraz 28% dla LR. Największy wpływ na stężenia NO2 w kanionie komunikacyjnym ma wiatr oraz natężenie ruchu. W modelowaniu maksymalnych wartości dobowych nabierają znaczenia temperatura powietrza oraz wilgotność względna powietrza. Przeważające zachodnie i północno-zachodnie wiatry we Wrocławiu skutecznie realizują koncepcję przewietrzania miasta w zakresie rozważanego skrzyżowania.

18

Obciążenie metody badawczej w odniesieniu do znowelizowanego wydania normy 17025

Majcher Domosław, Berger-Kirsz Joanna

Systemy Wspomagania w Inżynierii Produkcji

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2019

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Vol. 8, iss. 1

314--322

PL

Wyznaczenie obciążenia procedury pomiarowej umożliwia określenie wielkości i rodzaju błędów systematycznych, które można następnie wyeliminować przez wprowadzenie poprawki. Najlepszą metodą oszacowania tego parametru jest zastosowanie regresji liniowej. Wydanie nowej normy 17015 dotyczącej laboratoriów badawczych i wzorcujących narzuca w/w jednostkom zmianę podejścia w niektórych aspektach pracy. Jednym z regionów w których nastąpiły zmiany jest zachowanie spójności pomiarowej. W tym wypadku wyznaczanie obciążenia musi odbywać się z wykorzystaniem certyfikowanych materiałów odniesienia pochodzących od kompetentnego producenta. Zachowanie spójności pomiarowej wskazuje aby wyznaczona w celu oszacowania regresja liniowa była typu ważonej względem (X i Y).

EN

Determination of the measurement procedure statistical burden makes it possible to determine the rate and type of systematic errors, which can be eliminated by proper amendments. The best method to estimate this parameter is to use linear regression. The publication of the new standard no 17025 for testing and calibration laboratories imposes on the above-mentioned units a change of approach in some works’ aspects. The changes that were made refer as well the measurement consistency maintaining area. In this case, determination of the statistical burden must be carried out by using the certified data of comparison from reliable manufacturer. The maintenance of the measurement consistency indicates that the linear regression determined for the estimation has to be weighted illative to ( X and Y) type.

19

Using monthly rainfall data to estimate rainfall erosivity factor of Iraq

Al-Shamarti Hasanain K., Manji Osamah B., Albw Jbianah Mohanad I. K.

Przegląd Naukowy Inżynieria i Kształtowanie Środowiska

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2019

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Vol. 28, No. 3

444--454

EN

The erosivity factor have a major effect on soil therefor a lot off researchers are interested about it. Actually, the erosivity depend on rainfall that could be a main source to water which effect on soil. To understand the erosivity factor in Iraq, we attempt to explain erosivity factor throughout 30 years (1980–2010). Because of daily data of interval 15 and 30 min are not provided in this area, we used the Fournier modifi ed index (MFI) that based on monthly date of rainfall. Also, we applied linear regression equation between annual rainfall and the MFI to predict the variables and coeff cient of determination was calculated. The study period divided to three decades and spatial distribution by Kriging method was used to interpolate the MFI of study area which calculate by ArcGIS 10.4.1. The results show that in the northern zone of Iraq MFI maximum values were recorded and in the range of MFI above 160. Moreover, in Emadiyah station the MFI excessed 250, which means the erosivity factor has a big effect on soil in this zone. Whereas, in middle zone, the MFI has range 0–120 but most of years of study period recorded 0–90 of the MFI. In southern zone, the MFI was 0–60 therefore the erosivity factor was moderated or law. The linear regression models were found for each station of study area and only Emadiyah, Teleafer, Khanqin and Nasiriya have weak coefficient determination.

20

Reliability test of a GNSS onboard receiver in the kinematic mode

Ćwiklak Janusz, Krasuski Kamil, Grzegorzewski Marek

Annual of Navigation

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2019

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No. 26

106--113

EN

The article presents the results of the aircraft Cessna 172 positioning based on navigation solutions in the GPS and EGNOS (SBAS) tracking mode. The article makes a comparison of coordinate readings of the Cessna 172 in the ellipsoidal BLh frame. The verification of the coordinates of the aircraft Cessna 172 was used to assess the reliability of the GNSS satellite technique in aviation. In a research test, the navigation data were recorded by the onboard receiver Thales Mobile Mapper during an air test performed over the military aerodrome EPDE in Dęblin. Judging by the conducted investigations, it is possible to conclude that the difference in BLh coordinates of the aircraft Cessna 172 on the basis of the GPS solution and EGNOS (SBAS) solution equals, respectively: from -0.5 m to +3 m for component B; and from -2 m to +6 m for component L; from approximately -11 m to over +1 m for component h. In addition, the paper defines factors of dilution of precision PDOP, based on the GPS and EGNOS (SBAS) solutions. The average value of the PDOP coefficient for a solution in the tracking GPS mode was 2.7, whereas in the EGNOS (SBAS) tracking mode, it was equal to 2.8.