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Search results for: MODEL ORDER SELECTION
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Automated Reduced Model Order Selection
PublicationThis letter proposes to automate generation of reduced-order models used for accelerated -parameter computation by applying a posteriori model error estimators. So far,a posteriori error estimators were used in Reduced Basis Method (RBM) and Proper Orthogonal Decomposition (POD) to select frequency points at which basis vectors are generated. This letter shows how a posteriori error estimators can be applied to automatically select...
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Automatic Reduction-Order Selection for Finite-Element Macromodels
PublicationAn automatic reduction-order selection algorithm for macromodels in finite-element analysis is presented. The algorithm is based on a goal-oriented a posteriori error estimator that operates on low-order reduced blocks of matrices, and hence, it can be evaluated extremely quickly.
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Identification of nonstationary multivariate autoregressive processes– Comparison of competitive and collaborative strategies for joint selection of estimation bandwidth and model order
PublicationThe problem of identification of multivariate autoregressive processes (systems or signals) with unknown and possibly time-varying model order and time-varying rate of parameter variation is considered and solved using parallel estimation approach. Under this approach, several local estimation algorithms, with different order and bandwidth settings, are run simultaneously and compared based on their predictive performance. First,...
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On joint order and bandwidth selection for identification of nonstationary autoregressive processes
PublicationWhen identifying a nonstationary autoregressive process, e.g. for the purpose of signal prediction or parametric spectrum estimation, two important decisions must be taken. First, one should choose the appropriate order of the autoregressive model, i.e., the number of autoregressive coefficients that will be estimated. Second, if identification is carried out using the local estimation technique, such as the localized version of...
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Multilevel model order reduction.
PublicationPrezentujemy wielopoziomowy algorytm redukcji rzędu modelu wykorzystany do zwiększenia efektywnosci analizy struktur mikrofalowych metodami siatkowymi.Schemat pozwala tworzyć makromodele zagniezdzone i laczyc te technike z szybkim przemiataniem częstotliwości (FFS). Implementacja metody pokazana jest na przukladzie różnic skończonych w dziedzinie częstotliwości i metody redukcji ENOR, lecz koncept moze być łatwo użyty w innych...
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Reduced order model of 2d system
PublicationA new method of modelling is developed for static and dynamic analysis of two-dimensional elastic bodies. In the analysis, an elastic body is divided into strips. For each one-dimensional strip the reduced modal model is build up. The modal model contains appropriate number of inputs and outputs to connect lumped interaction that occur between strips. Proposed method of modelling enables to obtain more accurate and more simple...
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Model order reduction for subgridding in fdtd scheme
PublicationW artykule zaprezentowana została technika pozwalająca na uzyskanie wysokiej rozdzielczości w metodzie FDTD. Prezentowany algorytm jest połączeniem metod redukcji rzędu modelu i lokalnych zagęszczeń zaimplementowanych do FDTD. Pozwala to zmniejszyć liczbę użytych zmiennych stanu, a także skrócić krok czasowy, co skutkuje znacznie krótszym czasem symulacji, niż w przypadku klasycznej metody FDTD.
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Grouping macromodels by using multilevel model order reduction
Publicationartykuł pprezentuje nowatorską technikę grupowania makromodeli dla metody fdtd. nowa technika bazuje na schemacie wielopoziomowej redukcji rzędu modeli. grupowanie makromodeli pozwala na zwiększenie szybkości symulacji w porównaniu do niezgrupowanych makromodeli, zapewniając przy tym porównywalną dokładność.
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Time domain validation of ultracapacitor fractional order model
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Auditory-model based robust feature selection for speech recognition
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Deflated Preconditioned Solvers for Parametrized Local Model Order Reduction
PublicationOne of steps in the design of microwave filters is numerical tuning using full-wave simulators. Typically, it is a time-consuming process as it uses advanced computational methods, e.g. the finite-element method (FEM) and it usually requires multiple optimization steps before the specification goals are met. FEM involves solving a large sparse system of equations at many frequency points and therefore its computational cost is...
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Wideband Model Order Reduction for Macromodels in Finite Element Method
PublicationAbstract: This paper presents a novel algorithm for accelerating 3D Finite Element Method simulations by introducing macromodels created in local model order reduction in the selected subdomains of the computational domain. It generates the projection basis for a compact system of equations associated with a separate subdomain. Due to non-linear frequency dependency in the Right Hand Side (RHS), the standard reduction methods do...
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Spurious Modes in Model Order Reduction in Variational Problems in Electromagnetics
PublicationIn this work, we address an everlasting issue in 2 model order reduction (MOR) in electromagnetics that has 3 remained unnoticed until now. Contrary to what has been 4 previously done, we identify for the very first time spurious 5 modes in MOR for time-harmonic Maxwell’s equations and 6 propose a methodology to remove their negative influence on the 7 reduced order model (ROM) response. These spurious modes 8 have nonzero resonance...
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Model Order Reduction for Problems With Dispersive Surface Boundary Conditions
PublicationThis letter proposes a new scheme for reduced-order finite-element modeling of electromagnetic structures with nonlinear, dispersive surface boundary conditions, which optimally exploits the numerically stable and efficient MOR framework for second-order systems provided by SAPOR method. The presented results of numerical experiments for an example of a waveguide filter demonstrate the superior accuracy of the resulting reduced models...
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Hard Lessons Learned: A Model that Facilitates the Selection of Methods of IT Project Management
PublicationThe article presents the results of research conducted in an international enterprise responsible for IT project implementation. The carried out analysis of the case study with the use of surveys and data synthesis allowed the major factors causing problems connected with project management to be identified. The identified factors were aggregated and then, by using four key variables, a rhomboidal model adaptation was proposed...
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Implementing second-order CFA model for the factorial validity of brand equity
PublicationThe purpose of this study was to test the implementation of a second-order CFA model for the factorial validity of Aaker’s consumer-based brand equity framework. To test the proposed theoretical model 186 data sets generated through a standardized onlinesurvey were evaluated. The data wasanalyzedusing structural equation modeling with AMOS 21.0 software. The results demonstrated that the higher order CFA model for consumer-based...
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Efficient model order reduction for FEM analysis of waveguide structures and resonators
PublicationAn efficient model order reduction method for three-dimensional Finite Element Method (FEM) analysis of waveguide structures is proposed. The method is based on the Efficient Modal Order Reduction (ENOR) algorithm for creating macro-elements in cascaded subdomains. The resulting macro-elements are represented by very compact submatrices, leading to significant reduction of the overall number of unknowns. The efficiency of the model...
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Geometry Parametric Model Order Reduction with Randomly Generated Projection Bases
PublicationIn this work, a reduced-order model for geometry parameters and fast frequency sweep is proposed. The Finite Element Method is used to solve time-harmonic Maxwell’s equations. Taking into account the electromagnetic field does not arbitrarily vary as a function of frequency and geometry parameters, a low dimension system manifold is identified. Thus, the original Finite Element problem can be approximated by a model of reduced...
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A Model-Order Reduction Approach for Electromagnetic Problems With Nonaffine Frequency Dependence
PublicationThe aim of this paper is to present a novel model-order reduction (MOR) technique for the efcient frequency-domain nite-element method (FEM) simulation of microwave components. It is based on the standard reduced-basis method, but the subsequent expansion frequency points are selected following the so-called sparsied greedy strategy. This feature makes it especially useful to perform a fast-frequency sweep of problems that lead...
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Efficient analysis of structures with rotatable elements using model order reduction
PublicationThis paper presents a novel full-wave technique which allows for a fast 3D finite element analysis of waveguide structures containing rotatable tuning elements of arbitrary shapes. Rotation of these elements changes the resonant frequencies of the structure, which can be used in the tuning process to obtain the S-characteristics desired for the device. For fast commutations of the response as the tuning elements are rotated, the...
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Quality model for UML tools in application to UML tool selection and market analysis
PublicationJęzyki modelowania i wspierające je narzędzia odgrywają istotną rolę w procesie wytwarzania i utrzymania oprogramowania. Wraz ze wzrostem liczby narzędzi UML na rynku pojawia się potrzeba ich porównania i oceny. Artykuł prezentuje wielowymiarowy model oceny narzędzi UML, opisuje ankietę przydatną do oceny narzędzi UML oraz przedstawia system oceny narzędzi UML wraz ze studium przypadku jego zastosowania do poszukiwania narzędzi...
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Tree-based homogeneous ensemble model with feature selection for diabetic retinopathy prediction
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Comparison of Compact Reduced Basis Method with Different Model Order Reduction Techniques
PublicationDifferent strategies suitable to compare the performance of different model order reduction techniques for fast frequency sweep in finite element analysis in Electromagnetics are proposed and studied in this work. A Frobenius norm error measure is used to describe how good job a reduced-order model is doing with respect to the true system response. In addition, the transfer function correct behavior is monitored by studying the...
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Reliable Greedy Multipoint Model-Order Reduction Techniques for Finite-Element Analysis
PublicationA new greedy multipoint model-order reduction algorithm for fast frequency-domain finite-element method simulations of electromagnetic problems is proposed. The location of the expansion points and the size of the projection basis are determined based on a rigorous error estimator. Compared to previous multipoint methods, the quality of the error estimator is significantly improved by ensuring the orthogonality of the projection...
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Simulation model for evaluation of packet sequence changed order of stream in DiffServ network
PublicationCurrent packet networks use a large variety of mechanisms which should support QoS (Quality of Service). One of those mechanisms is routing (calculating connection paths for incoming service requests). The most effective mechanism in QoS context is dynamic routing, which is based on the current network state described by the offered traffic matrix and link states. After switching between calculated available paths, connection...
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Communication Model Order Reduction in Hybrid Methods Involving Generalized Impedance Matrix
PublicationA novel strategy for the efficient analysis of frequency-domain scattering electromagnetic problems in open and closed domains is presented. A fully automatic model-order reduction technique, called the enhanced reduced-basis method, is applied to increase the efficiency of the hybrid approach, which combines the finite-element and mode-matching methods. Numerical tests show that the proposed algorithm yields reliable and highly...
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Macro-elements and Model Order Reduction for Efficient Three-Dimensional FEM Analysis
PublicationAn efficient model order reduction (MOR) methodology for three dimensional vector finite element method (FEM) is developed to accelerate simulations of the structures containing features that cause strong variations of mesh density. As the result of presented algorithm, FEM subsystems of equations corresponding to the selected refined region are converted into a very compact sets of linear equations, called macro-elements.Numerical...
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Selection and Setting of an Intelligent Fuzzy Regulator based on Nonlinear Model Simulations of a Helicopter in Hover
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A Conception of Pairwise Comparisons Model for Selection of Appropriate Body Surface Area Calculation Formula
PublicationBody surface area (BSA) may be computed using a variety of formulas, but the computed BSA differs from real BSA values for particular subjects. This is presented in the paper by computing BSA values for selected subject and comparing them to the real BSA value obtained with the use of a 3D body scanner. The results show inequalities in the relevant BSA computing formulas. Hence, there is a need to determine a method that will allow...
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Greedy Multipoint Model-Order Reduction Technique for Fast Computation of Scattering Parameters of Electromagnetic Systems
PublicationThis paper attempts to develop a new automated multipoint model-order reduction (MOR) technique, based on matching moments of the system input–output function, which would be suited for fast and accurate computation of scattering parameters for electromagnetic (EM) systems over a wide frequency band. To this end, two questions are addressed. Firstly, the cost of the wideband reduced model generation is optimized by automating a...
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Compressed Projection Bases for Model-Order Reduction of Multiport Microwave Components Using FEM
PublicationThis paper presents a projection basis compression technique for generating compact reduced-order models (ROM) in the FE analysis of microwave devices. In this approach redundancy is removed from the projection basis by means of the proper orthogonal decomposition technique applied to the projected system of linear equations. Compression allows for keeping the size of a reduced-order model as small as possible without compromising...
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Fast frequency sweep based on the model order reduction technique for calculating scattering parametersjinjFDFDj
PublicationArtykuł prezentuje ulepszoną, efektywną metodę przemiatania częstotliwościowego dla metody FDFD. Liczba równań opisujących analizowaną strukturę jest redukowana za pomocą metody redukcjirzędu modeli, a następnie macierz wynikowa jest diagonalizowana. Kosztowne czasowo odwracanie dużych macierzy jest zastąpione prostym mnożeniem małej macierz diagonalnej przez wektor. Zaprezentowana metoda przemiatania częstotliwościowego może...
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Lattice filter based autoregressive spectrum estimation with joint model order and estimation bandwidth adaptation
PublicationThe problem of parametric, autoregressive model based estimation of a time-varying spectral density function of a nonstationary process is considered. It is shown that estimation results can be considerably improved if identification of the autoregressive model is carried out using the two-sided doubly exponentially weighted lattice algorithm which combines results yielded by two one-sided lattice algorithms running forward in...
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Multilevel model order reduction with generalized compression of boundaries for 3-d FEM electromagnetic analysis
PublicationThis paper presents a multilevel Model Order Reduction technique for a 3-D electromagnetic Finite Element Method analysis. The reduction process is carried out in a hierarchical way and involves several steps which are repeated at each level. This approach brings about versatility and allows one to efficiently analyze complex electromagnetic structures. In the proposed multilevel reduction the entire computational domain is covered...
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A Computationally Efficient Model for Predicting Successful Memory Encoding Using Machine-Learning-based EEG Channel Selection
PublicationComputational cost is an important consideration for memory encoding prediction models that use data from dozens of implanted electrodes. We propose a method to reduce computational expense by selecting a subset of all the electrodes to build the prediction model. The electrodes were selected based on their likelihood of measuring brain activity useful for predicting memory encoding better than chance (in terms of AUC). A logistic...
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Lattice filter based multivariate autoregressive spectral estimation with joint model order and estimation bandwidth adaptation
PublicationThe problem of parametric, autoregressive model based estimation of a time-varying spectral density function of a multivariate nonstationary process is considered. It is shown that estimation results can be considerably improved if identification of the autoregressive model is carried out using the two-sided doubly exponentially weighted lattice algorithm which combines results yielded by two one-sided lattice algorithms running...
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Thermomagnetic behavior of a semiconductor material heated by pulsed excitation based on the fourth-order MGT photothermal model
PublicationThis article proposes a photothermal model to reveal the thermo-magneto-mechanical properties of semiconductor materials, including coupled diffusion equations for thermal conductivity, elasticity, and excess carrier density. The proposed model is developed to account for the optical heating that occurs through the semiconductor medium. The Moore–Gibson–Thompson (MGT) equation of the fourth-order serves as the theoretical framework...
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Experiments on Preserving Pieces of Information in a Given Order in Holographic Reduced Representations and the Continuous Geometric Algebra Model
PublicationGeometric Analogues of Holographic Reduced Representations (GAc, which is the continuous version of the previously developed discrete GA model) employ role-filler binding based on geometric products.Atomic objects are real-valued vectors in n-dimensional Euclidean space and complex statements belong to a hierarchy of multivectors. The property of GAc and HRR studied here is the ability to store pieces of information in a given...
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An Attempt to Develop a Model Selection Algorithm of Computer Simulation during the Design Process of Mechanical Response of Any Mechanical Body
PublicationIn the literature, there are algorithms associated with the design of simulations of technological processes, in which the material model has always been defined previously. However, in none of the studies of computer simulation modelling of technological processes known to the authors of this article, is there a detailed description of how the algorithm, or the selection of plastic model used, is subject to this process. This...
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An attempt to develop a model selection algorithm of computer simulation during the design process of mechanical response of any mechanical body
Publicationn the literature, there are algorithms associated with the design of simulations of technological processes, in which the material model has always been defined previously. However, in none of the studies of computer simulation modelling of technological processes known to the authors of this article, is there a detailed description of how the algorithm, or the selection of plastic model used, is subject to this process. This article...
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Study of the Effectiveness of Model Order Reduction Algorithms in the Finite Element Method Analysis of Multi-port Microwave Structures
PublicationThe purpose of this paper is to investigate the effectiveness of model order reduction algorithms in finite element method analysis of multi-port microwave structures. Consideration is given to state of the art algorithms, i.e. compact reduced-basis method (CRBM), second-order Arnoldi method for passive-order reduction (SAPOR), reduced-basis methods (RBM) and subspace-splitting moment-matching MOR (SSMM-MOR)
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A Subspace-Splitting Moment-Matching Model-Order Reduction Technique for Fast Wideband FEM Simulations of Microwave Structures
PublicationThis article describes a novel model-order reduction (MOR) approach for efficient wide frequency band finite-element method (FEM) simulations of microwave components. It relies on the splitting of the system transfer function into two components: a singular one that accounts for the in-band system poles and a regular part that has no in-band poles. In order to perform this splitting during the reduction process, the projection...
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An inverse algorithm for contact heat conduction problems with an interfacial heat source based on a first-order thermocouple model
PublicationInverse problems of contact heat conduction with an interfacial heat source are common in various fields of science, engineering and technology. In this study, an algorithm for their solution is developed based on an inverse parametric optimisation method with an impulse response function describing the heat partition and contact heat transfer. A first-order thermocouple model with a time constant parameter is embedded in the impulse...
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Accurate Modeling of Frequency Selective Surfaces Using Fully-Connected Regression Model with Automated Architecture Determination and Parameter Selection Based on Bayesian Optimization
PublicationSurrogate modeling has become an important tool in the design of high-frequency structures. Although full-wave electromagnetic (EM) simulation tools provide an accurate account for the circuit characteristics and performance, they entail considerable computational expenditures. Replacing EM analysis by fast surrogates provides a way to accelerate the design procedures. Unfortunately, modeling of microwave passives is a challenging...
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Comparison and Analysis of Service Selection Algorithms
PublicationIn Service Oriented Architecture, applications are developed by integration of existing services in order to reduce development cost and time. The approach, however, requires algorithms that select appropriate services out of available, alternative ones. The selection process may consider both optimalization requirements, such as maximalization of performance, and constraint requirements, such minimal security or maximum development...
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Project Team Management Supported by an Agent-Based Model
PublicationThis work is a continuation of a series of works about research into the use of multi-agent systems to support IT project management. Previous studies have shown the possibility of using a multi-agent in order to optimize management decisions concerning the selection of methods for project implementation. It was noted that the project manager's decisions are influenced by three fundamental parameters: the entropy of the project,...
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Estimation of the size of informal employment based on administrative records with non‐ignorable selection mechanism
PublicationIn this study, we used company level administrative data from the National Labour Inspectorate and The Polish Social Insurance Institution in order to estimate the prevalence of informal employment in Poland in 2016. Since the selection mechanism is non‐ignorable, we employed a generalization of Heckman’s sample selection model assuming non‐Gaussian correlation of errors and clustering by incorporation of random effects. We found...
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On Noncausal Identification of Nonstationary Multivariate Autoregressive Processes
PublicationThe 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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Physical and mathematical modelling of implant-fascia system in order to improve laparoscopic repair of ventral hernia
PublicationThis paper describes an investigation of biomechanical behaviour of hernia repair, which is focused on the selection of safe linking of certain type of implant with fascia in laparoscopic operation. The strength of various fixations of the implant to the fascia is analysed. Methods: The research is based on experimental observations of operated hernia model behaviour during a dynamic impulse load corresponding to post-operative...
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Soft Sensor Application in Identification of the Activated Sludge Bulking Considering the Technological and Economical Aspects of Smart Systems Functioning
PublicationThe paper presented the methodology for the construction of a soft sensor used for activated sludge bulking identification. Devising such solutions fits within the current trends and development of a smart system and infrastructure within smart cities. In order to optimize the selection of the data-mining method depending on the data collected within a wastewater treatment plant (WWTP), a number of methods were considered, including:...