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Wyniki wyszukiwania dla: MULTIVARIATE LINEAR REGRESSION
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Electrochemical Production of Sodium Hypochlorite from Salty Wastewater Using a Flow-by Porous Graphite Electrode
PublikacjaThe production of sodium hypochlorite (NaOCl) from salty wastewater using an electrochemical cell has several advantages over other methods that often require hazardous chemicals and generate toxic waste, being more sustainable and environmentally friendly. However, the process of producing sodium hypochlorite using an electrochemical cell requires careful control of the operating conditions, such as the current density, flow rate,...
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An algorithm for selecting a machine learning method for predicting nitrous oxide emissions in municipal wastewater treatment plants
PublikacjaThis study presents an advanced algorithm for selecting machine learning (ML) models for nitrous oxide (N2O) emission prediction in wastewater treatment plants (WWTPs) employing the activated sludge process. The examined ML models comprised multivariate adaptive regression spline (MARS), support vector machines (SVM), and extreme gradient boosting (XGboost). The study explores the concept that involves new criteria to select the...
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Determination of benzo(a)pyrene content in PM10 using regression methods
PublikacjaThe paper presents an attempt of application of multidimensional linear regression to estimation of an empirical model describing the factors influencing on B(a)P content in suspended dust PM10 in Olsztyn and Elbląg city regions between 2010 and 2013. During this period annual average concentration of B(a)P in PM10 exceeded the admissible level 1.5-3 times. Conducted investigations confirm that the reasons of B(a)P concentration...
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On Noncausal Identification of Nonstationary Multivariate Autoregressive Processes
PublikacjaThe problem of identification of nonstationary multivariate autoregressive processes using noncausal local estimation schemes is considered and a new approach to joint selection of the model order and the estimation bandwidth is proposed. The new selection rule, based on evaluation of pseudoprediction errors, is compared with the previously proposed one, based on the modified Akaike’s final prediction error criterion.
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Classification and fingerprinting of kiwi and pomelo fruits by multivariate analysis of chromatographic and spectroscopic data
PublikacjaThe fingerprinting capacity of two analytical techniques, HPLC and UV-Vis spectroscopy in the case of fruits samples (kiwi and pomelo) has been investigated. The multivariate exploratory techniques were used for sample discrimination according to the fruit species and subspecies. The combination of principal component analysis with linear discriminant analysis is opening new directions in the fingerprinting analysis. The classifications...
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Efficiency of linear and non-linear classifiers for gas identification from electrocatalytic gas sensor
PublikacjaElectrocatalytic gas sensors belong to the family of electrochemical solid state sensors. Their responses are acquired in the form of I-V plots as a result of application of cyclic voltammetry technique. In order to obtain information about the type of measured gas the multivariate data analysis and pattern classification techniques can be employed. However, there is a lack of information in literature about application of such...
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Buried Object Characterization by Data-Driven Surrogates and Regression-Enabled Hyperbolic Signature Extraction
PublikacjaThis work addresses artificial-intelligence-based buried object characterization using FDTD-based electromagnetic simulation toolbox of a Ground Penetrating Radar (GPR) to generate B-scan data. In data collection, FDTD-based simulation tool, gprMax is used. The task is to estimate geophysical parameters of a cylindrical shape object of various radii, buried at different positions in the dry soil medium simultaneously and independently...
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Towards Designing an Innovative Industrial Fan: Developing Regression and Neural Models Based on Remote Mass Measurements
PublikacjaThis article presents the process of the construction and testing a remote, fully autonomous system for measuring the operational parameters of fans. The measurement results obtained made it possible to create and verify mathematical models using linear regression and neural networks. The process was implemented as part of the first stage of an innovative project. The article presents detailed steps of constructing a system to...
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JOURNAL OF MULTIVARIATE ANALYSIS
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Multivariate Behavioral Research
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On Adaptive Spectrum Estimation of Multivariate Autoregressive Locally Stationary Processes
PublikacjaAutoregressive modeling is a widespread parametricspectrum estimation method. It is well known that, in the caseof stationary processes with unknown order, its accuracy canbe improved by averaging models of different complexity usingsuitably chosen weights. The paper proposes an extension of thistechnique to the case of multivariate locally stationary processes.The proposed solution is based on local autoregressive...
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Regression points in non-intrusive polynomial chaos expansion method and D-optimal design
PublikacjaThe paper addresses selected issues of uncertainty quantification in the modelling of a system containing surgical mesh used in ventral hernia repair. Uncertainties in the models occur e.g. due to variability of abdominal wall properties among others. In order to include them, a non-intrusive regression-based polynomial chaos expansion method is employed. Its accuracy depends on the choice of regression points. In the study a relation...
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Application of multivariate statistics in assessment of green analytical chemistry parameters of analytical methodologies
PublikacjaThe study offers a multivariate statistical analysis of a dataset, including the major metrological, “greenness” and methodological parameters of 43 analytical methodologies applied for aldrin determination (a frequently analyzed organic compound) in water samples. The variables (parameters) chosen were as follows: metrological (LOD, recovery, RSD), describing the “greenness” (amount of the solvent used, amount of waste generated)...
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Sensitivity analysis based on non-intrusive regression-based polynomial chaos expansion for surgical mesh modelling
PublikacjaThe modelling of a system containing implants used in ventral hernia repair and human tissue suffers from many uncertainties. Thus, a probabilistic approach is needed. The goal of this study is to define an efficient numerical method to solve non-linear biomechanical models supporting the surgeon in decisions about ventral hernia repair. The model parameters are subject to substantial variability owing to, e.g., abdominal wall...
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Multivariate analysis of impedance data obtained for coating systems of varying thickness applied on steel
PublikacjaElectrochemical impedance spectroscopy (EIS) has proven to be a valuable test method for the electrochemical characterization of protective coatings on metals. The common way of analysis in impedance spectroscopy is to model the impedance spectrum by means of an equivalent circuit and to extract the quantity of interest using optimization techniques. A model, corresponding to the behavior of the sample under testing, is important...
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Reducing Monitoring Costs in Industrially Contaminated Rivers: Cluster and Regression Analysis Approach
PublikacjaMonitoring contamination in river water is an expensive procedure, particularly for developing countries where pollution is a significant problem. This study was conducted to provide a pollution monitoring strategy that reduces the cost of laboratory analysis. The new monitoring strategy was designed as a result of cluster and regression analysis on field data collected from an industrially influenced river. Pollution sources in...
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On adaptive covariance and spectrum estimation of locally stationary multivariate processes
PublikacjaWhen estimating the correlation/spectral structure of a locally stationary process, one has to make two important decisions. First, one should choose the so-called estimation bandwidth, inversely proportional to the effective width of the local analysis window, in the way that complies with the degree of signal nonstationarity. Too small bandwidth may result in an excessive estimation bias, while too large bandwidth may cause excessive...
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LINEAR & MULTILINEAR ALGEBRA
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Regularized Local Multivariate Reduced-Order Models With Nonaffine Parameter Dependence
PublikacjaThis paper addresses a singular problem, not yet discussed in the literature, which occurs when parametric reduced-order models are created using a subspace projection approach with multiple concatenated projection bases. We show that this technique may lead to the appearance of localized artifacts in the frequency characteristics of a system, even when the reduced-order projection basis is rich enough to describe the original...
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Comparison of non-linear statical analysis of truss with linear and rotational side supports and 3d roof model
PublikacjaIn the paper geometrically non-linear analysis of example truss with linear and rotational elastic side supports is compared with geometrically non-linear analysis of part of the roof construction with purlins and truss-bracing. For different stiffness of side-supports a non linear relation between normal force in compressed chord due to out of truss plane displacement has been calculated.