Relevant bibliographies by topics / Additive decomposition model

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'Additive decomposition model'

Author: Grafiati
Published: 4 June 2021
Last updated: 1 February 2022

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Journal articles on the topic "Additive decomposition model"

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Brauer, Elizabeth J., Marek Turowski, and James M. McDonough. "Additive Decomposition Applied to the Semiconductor Drift-Diffusion Model." VLSI Design 8, no. 1-4 (1998): 393–99. http://dx.doi.org/10.1155/1998/96170.

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A new numerical method for semiconductor device simulation is presented. The additive decomposition method has been successfully applied to Burgers' and Navier-Stokes equations governing turbulent fluid flow by decomposing the equations into large-scale and small-scale parts without averaging. The additive decomposition (AD) technique is well suited to problems with a large range of time and/or space scales, for example, thermal-electrical simulation of power semiconductor devices with large physical size. Furthermore, AD adds a level of parallelization for improved computational efficiency. The new numerical technique has been tested on the 1-D drift-diffusion model of a p-i-n diode for reverse and forward biases. Distributions of φ, n and p have been calculated using the AD method on a coarse large-scale grid and then in parallel small-scale grid sections. The AD results agreed well with the results obtained with a traditional one-grid approach, while potentially reducing memory requirements with the new method.
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Abrashina-Zhadaeva, N., and N. Romanova. "Vector Additive Decomposition for 2D Fractional Diffusion Equation." Nonlinear Analysis: Modelling and Control 13, no. 2 (2008): 137–43. http://dx.doi.org/10.15388/na.2008.13.2.14574.

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Such physical processes as the diffusion in the environments with fractal geometry and the particles’ subdiffusion lead to the initial value problems for the nonlocal fractional order partial differential equations. These equations are the generalization of the classical integer order differential equations. 
 An analytical solution for fractional order differential equation with the constant coefficients is obtained in [1] by using Laplace-Fourier transform. However, nowadays many of the practical problems are described by the models with variable coefficients. 
 In this paper we discuss the numerical vector decomposition model which is based on a shifted version of usual Gr¨unwald finite-difference approximation [2] for the non-local fractional order operators. We prove the unconditional stability of the method for the fractional diffusion equation with Dirichlet boundary conditions. Moreover, a numerical example using a finite difference algorithm for 2D fractional order partial differential equations is also presented and compared with the exact analytical solution.
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Ang, Sheng, and Chien-Ming Chen. "Pitfalls of decomposition weights in the additive multi-stage DEA model." Omega 58 (January 2016): 139–53. http://dx.doi.org/10.1016/j.omega.2015.05.008.

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Emmanuel, Biu O., Dennis Enegesele, and C. O. Arimie. "Additive Decomposition with Arima Model Forecasts When the Trend Component Is Quadratic." OALib 07, no. 07 (2020): 1–20. http://dx.doi.org/10.4236/oalib.1106435.

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Liu, Wenyang, Ling Chen, Guangzhen Mai, and Lijun Song. "Toolpath planning for additive manufacturing using sliced model decomposition and metaheuristic algorithms." Advances in Engineering Software 149 (November 2020): 102906. http://dx.doi.org/10.1016/j.advengsoft.2020.102906.

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Tian, Yongge. "On an additive decomposition of the BLUE in a multiple-partitioned linear model." Journal of Multivariate Analysis 100, no. 4 (2009): 767–76. http://dx.doi.org/10.1016/j.jmva.2008.08.006.

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NGUYEN, Lam, Johannes BUHL, and Markus BAMBACH. "DECOMPOSITION ALGORITHM FOR TOOL PATH PLANNING FOR WIRE-ARC ADDITIVE MANUFACTURING." Journal of Machine Engineering Vol.18, No.1 (2018): 96–107. http://dx.doi.org/10.5604/01.3001.0010.8827.

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Three-axis machines are limited in the production of geometrical features in powder-bed additive manufacturing processes. In case of overhangs, support material has to be added due to the nature of the process, which causes some disadvantages. Robot-based wire-arc additive manufacturing (WAAM) is able to fabricate overhangs without adding support material. Hence, build time, waste of material, and post-processing might be reduced considerably. In order to make full use of multi-axis advantages, slicing strategies are needed. To this end, the CAD (computer-aided design) model of the part to be built is first partitioned into sub-parts, and for each sub-part, an individual build direction is identified. Path planning for these sub-parts by slicing then enables to produce the parts. This study presents a heuristic method to deal with the decomposition of CAD models and build direction identification for sub-entities. The geometric data of two adjacent slices are analyzed to construct centroidal axes. These centroidal axes are used to navigate the slicing and building processes. A case study and experiments are presented to exemplify the algorithm.
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Mørup, Morten, Lars Kai Hansen, and Sidse M. Arnfred. "Algorithms for Sparse Nonnegative Tucker Decompositions." Neural Computation 20, no. 8 (2008): 2112–31. http://dx.doi.org/10.1162/neco.2008.11-06-407.

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There is a increasing interest in analysis of large-scale multiway data. The concept of multiway data refers to arrays of data with more than two dimensions, that is, taking the form of tensors. To analyze such data, decomposition techniques are widely used. The two most common decompositions for tensors are the Tucker model and the more restricted PARAFAC model. Both models can be viewed as generalizations of the regular factor analysis to data of more than two modalities. Nonnegative matrix factorization (NMF), in conjunction with sparse coding, has recently been given much attention due to its part-based and easy interpretable representation. While NMF has been extended to the PARAFAC model, no such attempt has been done to extend NMF to the Tucker model. However, if the tensor data analyzed are nonnegative, it may well be relevant to consider purely additive (i.e., nonnegative) Tucker decompositions). To reduce ambiguities of this type of decomposition, we develop updates that can impose sparseness in any combination of modalities, hence, proposed algorithms for sparse nonnegative Tucker decompositions (SN-TUCKER). We demonstrate how the proposed algorithms are superior to existing algorithms for Tucker decompositions when the data and interactions can be considered nonnegative. We further illustrate how sparse coding can help identify what model (PARAFAC or Tucker) is more appropriate for the data as well as to select the number of components by turning off excess components. The algorithms for SN-TUCKER can be downloaded from Mørup (2007).
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Fujimoto, Katsushige, Toshiaki Murofushi, and Michio Sugeno. "Canonical Hierarchical Decomposition of Choquet Integral Over Finite Set with Respect to Null Additive Fuzzy Measure." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 06, no. 04 (1998): 345–63. http://dx.doi.org/10.1142/s021848859800029x.

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In this paper, we provide the necessary and sufficient condition for a Choquet integral model to be decomposable into a canonical hierarchical Choquet integral model constructed by hierarchical combinations of some ordinary Choquet integral models. This condition is characterized by the pre-Znclusion-Exclusion Covering (pre-IEC). Moreover, we show that the pre-IEC is the subdivision of an IEC and that the additive hierarchical structure is the most fundamental one on considering a hierarchical decomposition of the Choquet integral model.
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Velíšek, J., P. Calta, C. Crews, S. Hasnip, and M. Doležal. "3-Chloropropane-1,2-diol in models simulating processed foods: Precursors and agents causing its decomposition." Czech Journal of Food Sciences 21, No. 5 (2011): 153–61. http://dx.doi.org/10.17221/3493-cjfs.

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Formation of 3-chloropropane-1,2-diol (3-MCPD) was studied in model mixtures consisting of sodium chloride and either glycerol or various lipids (phospholipids, monoacylglycerols, diacylglycerols, triacylglycerols) derived mainly from palmitic and oleic acids. The average amount of 3-MCPD formed from these precursors after 30 min of heating at 200°C was from 9.7 (lecithin), to 5.1 (diacylglycerols), 4.7 (glycerol), 3.1 (triacylglycerols), and 2.9 (monoacylglycerols) µmol/mol, respectively. The formation of 3-MCPD from glycerol (one of the major precursors) was also studied in the presence of glutathione, cysteine, disodium carbonate and sodium bicarbonate, i.e. compounds having the potential to decompose 3-MCPD or to prevent its formation. The compound the most active in preventing the formation of 3-MCPD was sodium bicarbonate followed by disodium carbonate, cysteine and glutathione. The addition of glutathione lowered the level of 3-MCPD produced from glycerol and NaCl to approximately 80%, of cysteine to 42%, of disodium carbonate to 14%, and of sodium bicarbonate to as little as 8% in comparison to samples with no additive.
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Dissertations / Theses on the topic "Additive decomposition model"

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Bible, Stewart Andrew. "STUDY OF THE "POOR MAN'S NAVIER-STOKES" EQUATION TURBULENCE MODEL." UKnowledge, 2003. http://uknowledge.uky.edu/gradschool_theses/310.

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The work presented here is part of an ongoing effort to develop a highly accurate and numerically efficient turbulence simulation technique. The paper consists of four main parts, viz., the general discussion of the procedure known as Additive Turbulent Decomposition, the derivation of the "synthetic velocity" subgrid-scale model of the high wavenumber turbulent fluctuations necessary for its implementation, the numerical investigation of this model and a priori tests of said models physical validity. Through these investigations we have demonstrated that this procedure, coupled with the use of the "Poor Mans Navier-Stokes" equation subgrid-scale model, has the potential to be a faster, more accurate replacement of currently popular turbulence simulation techniques since: 1. The procedure is consistent with the direct solution of the Navier-Stokes equations if the subgrid-scale model is valid, i.e, the equations to be solved are never filtered, only solutions. 2. Model parameter values are "set" by their relationships to N.S. physics found from their derivation from the N.S. equation and can be calculated "on the fly" with the use of a local high-pass filtering of grid-scale results. 3. Preliminary studies of the PMNS equation model herein have shown it to be a computationally inexpensive and a priori valid model in its ability to reproduce high wavenumber fluctuations seen in an experimental turbulent flow.
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Akhmadishina, Alina. "Predikce vývoje diagnostických veličin." Master's thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2012. http://www.nusl.cz/ntk/nusl-230272.

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The work deals with the analysis of time series of diagnostic quantities measured in power oil transformers. The first part includes power oil transformers and the description of diagnostic variables that are measured inside these non-rotating electrical machines. The next section introduces the decomposition model of time series including analysis of all its components. The last part deals with the predictions of the likely survival time of power oil transformers operating in different power plants in the Czech Republic.
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Rios, Ricardo Araújo. "Improving time series modeling by decomposing and analysing stochastic and deterministic influences." Universidade de São Paulo, 2013. http://www.teses.usp.br/teses/disponiveis/55/55134/tde-18112013-143708/.

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This thesis presents a study on time series analysis, which was conducted based on the following hypothesis: time series influenced by additive noise can be decomposed into stochastic and deterministic components in which individual models permit obtaining a hybrid one that improves accuracy. This hypothesis was confirmed in two steps. In the first one, we developed a formal analysis using the Nyquist-Shannon sampling theorem, proving Intrinsic Mode Functions (IMFs) extracted from the Empirical Mode Decomposition (EMD) method can be combined, according to their frequency intensities, to form stochastic and deterministic components. Considering this proof, we designed two approaches to decompose time series, which were evaluated in synthetic and real-world scenarios. Experimental results confirmed the importance of decomposing time series and individually modeling the deterministic and stochastic components, proving the second part of our hypothesis. Furthermore, we noticed the individual analysis of both components plays an important role in detecting patterns and extracting implicit information from time series. In addition to these approaches, this thesis also presents two new measurements. The first one is used to evaluate the accuracy of time series modeling in forecasting observations. This measurement was motivated by the fact that existing measurements only consider the perfect match between expected and predicted values. This new measurement overcomes this issue by also analyzing the global time series behavior. The second measurement presented important results to assess the influence of the deterministic and stochastic components on time series observations, supporting the decomposition process. Finally, this thesis also presents a Systematic Literature Review, which collected important information on related work, and two new methods to produce surrogate data, which permit investigating the presence of linear and nonlinear Gaussian processes in time series, irrespective of the influence of nonstationary behavior<br>Esta tese apresenta um estudo sobre análise de séries temporais, a qual foi conduzida baseada na seguinte hipótese: séries temporais influenciadas por ruído aditivo podem ser decompostas em componentes estocásticos e determinísticos que ao serem modelados individualmente permitem obter um modelo híbrido de maior acurácia. Essa hipótese foi confirmada em duas etapas. Na primeira, desenvolveu-se uma análise formal usando o teorema de amostragem proposto por Nyquist-Shannon, provando que IMFs (Intrinsic Mode Functions) extraídas pelo método EMD (Empirical Mode Decomposition) podem ser combinadas de acordo com suas intensidades de frequência para formar os componentes estocásticos e determinísticos. Considerando essa prova, duas abordagens de decomposição de séries foram desenvolvidas e avaliadas em aplicações sintéticas e reais. Resultados experimentais confirmaram a importância de decompor séries temporais e modelar seus componentes estocásticos e determinísticos, provando a segunda parte da hipótese. Além disso, notou-se que a análise individual desses componentes possibilita detectar padrões e extrair importantes informações implícitas em séries temporais. Essa tese apresenta ainda duas novas medidas. A primeira é usada para avaliar a acurácia de modelos utilizados para predizer observações. A principal vantagem dessa medida em relação às existentes é a possibilidade de avaliar os valores individuais de predição e o comportamento global entre as observações preditas e experadas. A segunda medida permite avaliar a influência dos componentes estocásticos e determinísticos sobre as séries temporais. Finalmente, essa tese apresenta ainda resultados obtidos por meio de uma revisão sistemática da literatura, a qual coletou importantes trabalhos relacionados, e dois novos métodos para geração de dados substitutos, permitindo investigar a presença de processos Gaussianos lineares e não-lineares, independente da influência de comportamento não-estacionário
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Books on the topic "Additive decomposition model"

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Congendo, Marco, and Fernando H. Lopes da Silva. Event-Related Potentials. Edited by Donald L. Schomer and Fernando H. Lopes da Silva. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780190228484.003.0039.

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Event-related potentials (ERPs) can be elicited by a variety of stimuli and events in diverse conditions. This chapter covers the methodology of analyzing and quantifying ERPs in general. Basic models (additive, phase modulation and resetting, potential asymmetry) that account for the generation of ERPs are discussed. The principles and requirements of ensemble time averaging are presented, along with several univariate and multivariate methods that have been proposed to improve the averaging procedure: wavelet decomposition and denoising, spatial, temporal and spatio-temporal filtering. We emphasize basic concepts of principal component analysis, common spatial pattern, and blind source separation, including independent component analysis. We cover practical questions related to the averaging procedure: overlapping ERPs, correcting inter-sweep latency and amplitude variability, alternative averaging methods (e.g., median), and estimation of ERP onset. Some specific aspects of ERP analysis in the frequency domain are surveyed, along with topographic analysis, statistical testing, and classification methods.
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Book chapters on the topic "Additive decomposition model"

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Balin, Nolwenn, Abderrahmane Bendali, and Francis Collino. "Domain Decomposition and Additive Schwarz Techniques in the Solution of a TE Model of the Scattering by an Electrically Deep Cavity." In Lecture Notes in Computational Science and Engineering. Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/3-540-26825-1_11.

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Loosen, Simon, Matthias Meinke, and Wolfgang Schröder. "Numerical Analysis of the Turbulent Wake for a Generic Space Launcher with a Dual-Bell Nozzle." In Notes on Numerical Fluid Mechanics and Multidisciplinary Design. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-53847-7_10.

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Abstract The turbulent wake of an axisymmetric generic space launcher equipped with a dual-bell nozzle is simulated at transonic ($$Ma_\infty = 0.8$$ and $$Re_D = 4.3\cdot 10^5$$) and supersonic ($$Ma_\infty = 3$$ and $$Re_D = 1.2\cdot 10^6$$) freestream conditions, to investigate the influence of the dual-bell nozzle jet onto the wake flow and vice versa. In addition, flow control by means of four in circumferential direction equally distributed jets injecting air encountering the backflow in the recirculation region is utilized to determine if the coherence of the wake and consequently, the buffet loads can be reduced by flow control. The simulations are performed using a zonal RANS/LES approach. The time-resolved flow field data are analyzed by classical spectral analysis, two-point correlation analysis, and dynamic mode decomposition (DMD). At supersonic freestream conditions, the nozzle counter pressure is reduced by the expansion of the outer flow around the nozzle lip leading to a decreased transition nozzle pressure ratio. In the transonic configuration a spatio-temporal mode with an eigenvalue matching the characteristic buffet frequency of $$Sr_D=0.2$$ is extracted by the spectral and DMD analysis. The spatial shape of the detected mode describes an antisymmetric wave-like undulating motion of the shear layer inducing the low frequency dynamic buffet loads. By flow control this antisymmetric coherent motion is weakened leading to a reduction of the buffet loads on the nozzle fairing.
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Anand, Lallit, and Sanjay Govindjee. "Three-dimensional plasticity with kinematic and isotropic hardening." In Continuum Mechanics of Solids. Oxford University Press, 2020. http://dx.doi.org/10.1093/oso/9780198864721.003.0022.

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This chapter provides an introduction to combined isotropic-kinematic hardening plasticity models in the three-dimensional small strain setting. The additive decomposition of the strain is introduced along with the concepts of plastic strain, equivalent tensile plastic strain, and back stress for three-dimensional problems. Plastic flow is discussed and defined, and a complete model of plasticity is formulated with Kuhn-Tucker loading/unloading conditions. The kinematic hardening model is based upon the Armstrong-Fredrick evolution law. Both rate-independent and rate-dependent (viscoplastic) models are discussed.
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Anand, Lallit, and Sanjay Govindjee. "Three-dimensional plasticity with isotropic hardening." In Continuum Mechanics of Solids. Oxford University Press, 2020. http://dx.doi.org/10.1093/oso/9780198864721.003.0021.

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This chapter provides an introduction to isotropic hardening plasticity models in the three-dimensional small strain setting. The additive decomposition of the strain is introduced along with the concepts of plastic strain and equivalent tensile plastic strain for three-dimensional problems. Plastic flow is discussed and defined, and a complete model of plasticity is formulated with Kuhn-Tucker loading/unloading conditions. Both rate independent and rate dependent (viscoplastic) models are discussed with an emphasis on Mises-Hill type theories which utilizes a Prandtl-Reuss flow rule. A variety of important flow models are presented.
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Anand, Lallit, and Sanjay Govindjee. "One-dimensional plasticity." In Continuum Mechanics of Solids. Oxford University Press, 2020. http://dx.doi.org/10.1093/oso/9780198864721.003.0020.

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This chapter provides an introduction to plasticity models in the one-dimensional setting. The phenomenology of plasticity is discussed together with concepts of isotropic and kinematic hardening. The additive decomposition of the strain is introduced along with the concepts of plastic strain and equivalent plastic strain. Plastic flow is discussed and defined, and complete models of plasticity are formulated with loading/unloading conditions. Both rate independent and rate dependent (viscoplastic) models are discussed. In addition, basic numerical methods for evaluating plasticity models are presented.
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Abdelouahad, Abdelkaher Ait, Mohammed El Hassouni, Hocine Cherifi, and Driss Aboutajdine. "A New Image Distortion Measure Based on Natural Scene Statistics Modeling." In Geographic Information Systems. IGI Global, 2013. http://dx.doi.org/10.4018/978-1-4666-2038-4.ch037.

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In the field of Image Quality Assessment (IQA), this paper examines a Reduced Reference (RRIQA) measure based on the bi-dimensional empirical mode decomposition. The proposed measure belongs to Natural Scene Statistics (NSS) modeling approaches. First, the reference image is decomposed into Intrinsic Mode Functions (IMF); the authors then use the Generalized Gaussian Density (GGD) to model IMF coefficients distribution. At the receiver side, the same number of IMF is computed on the distorted image, and then the quality assessment is done by fitting error between the IMF coefficients histogram of the distorted image and the GGD estimate of IMF coefficients of the reference image, using the Kullback Leibler Divergence (KLD). In addition, the authors propose a new Support Vector Machine-based classification approach to evaluate the performances of the proposed measure instead of the logistic function-based regression. Experiments were conducted on the LIVE dataset.
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Floudas, Christodoulos A. "Mixed-Integer Nonlinear Optimization." In Nonlinear and Mixed-Integer Optimization. Oxford University Press, 1995. http://dx.doi.org/10.1093/oso/9780195100563.003.0011.

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This chapter presents the fundamentals and algorithms for mixed-integer nonlinear optimization problems. Sections 6.1 and 6.2 outline the motivation, formulation, and algorithmic approaches. Section 6.3 discusses the Generalized Benders Decomposition and its variants. Sections 6.4, 6.5 and 6.6 presents the Outer Approximation and its variants with Equality Relaxation and Augmented Penalty. Section 6.7 discusses the Generalized Outer Approximation while section 6.8 compares the Generalized Benders Decomposition with the Outer Approximation. Finally, section 6.9 discusses the Generalized Cross Decomposition. A wide range of nonlinear optimization problems involve integer or discrete variables in addition to the continuous variables. These classes of optimization problems arise from a variety of applications and are denoted as Mixed-Integer Nonlinear Programming MINLP problems. The integer variables can be used to model, for instance, sequences of events, alternative candidates, existence or nonexistence of units (in their zero-one representation), while discrete variables can model, for instance, different equipment sizes. The continuous variables are used to model the input-output and interaction relationships among individual units/operations and different interconnected systems. The nonlinear nature of these mixed-integer optimization problems may arise from (i) nonlinear relations in the integer domain exclusively (e.g., products of binary variables in the quadratic assignment model), (ii) nonlinear relations in the continuous domain only (e.g., complex nonlinear input-output model in a distillation column or reactor unit), (iii) nonlinear relations in the joint integer-continuous domain (e.g., products of continuous and binary variables in the scheduling/ planning of batch processes, and retrofit of heat recovery systems). In this chapter, we will focus on nonlinearities due to relations (ii) and (iii). An excellent book that studies mixed-integer linear optimization, and nonlinear integer relationships in combinatorial optimization is the one by Nemhauser and Wolsey (1988). The coupling of the integer domain with the continuous domain along with their associated nonlinearities make the class of MINLP problems very challenging from the theoretical, algorithmic,and computational point of view. Apart from this challenge, however, there exists a broad spectrum of applications that can be modeled as mixed-integer nonlinear programming problems.
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McCann, Kevin S. "Adding the Ecosystem." In Food Webs (MPB-50). Princeton University Press, 2011. http://dx.doi.org/10.23943/princeton/9780691134178.003.0011.

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This chapter examines how nutrient recycling and decomposition affect the dynamics and stability of food webs. It first reviews some of the existing theory on detritus and food web dynamics before discussing the basics of a model that takes into account grazing food webs and whole ecosystems. It then describes the N-R-D (nutrient pool, resource, detritus) submodule as well as the full N-C-R-D (nutrient pool, consumer, resource, detritus) model. It also explores how detritus may act to distribute nutrients by considering a model that begets nonequilibrium dynamics. It shows that detritus tends to stabilize consumer–resource interactions relative to the purely community module (no recycling) because the detritus tends to fall out of phase with the resource–nutrient interaction. The addition of a consumer–resource incteraction to the N-R-D module, even in a closed system, eventually can drive overshoot dynamics and destabilization by increased production, coupling, or interaction strength.
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Chan, Veronica, and Christine W. Chan. "Towards Developing the Piece-Wise Linear Neural Network Algorithm for Rule Extraction." In Deep Learning and Neural Networks. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-7998-0414-7.ch091.

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This paper discusses development and application of a decomposition neural network rule extraction algorithm for nonlinear regression problems. The algorithm is called the piece-wise linear artificial neural network or PWL-ANN algorithm. The objective of the algorithm is to “open up” the black box of a neural network model so that rules in the form of linear equations are generated by approximating the sigmoid activation functions of the hidden neurons in an artificial neural network (ANN). The preliminary results showed that the algorithm gives high fidelity and satisfactory results on sixteen of the nineteen tested datasets. By analyzing the values of R2 given by the PWL approximation on the hidden neurons and the overall output, it is evident that in addition to accurate approximation of each individual node of a given ANN model, there are more factors affecting the fidelity of the PWL-ANN algorithm Nevertheless, the algorithm shows promising potential for domains when better understanding about the problem is needed.
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Lei, Min. "Symplectic Geometry and Its Applications on Time Series Analysis." In Topology [Working Title]. IntechOpen, 2020. http://dx.doi.org/10.5772/intechopen.94958.

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This chapter serves to introduce the symplectic geometry theory in time series analysis and its applications in various fields. The basic concepts and basic elements of mathematics relevant to the symplectic geometry are introduced in the second section. It includes the symplectic space, symplectic transformation, Hamiltonian matrix, symplectic principal component analysis (SPCA), symplectic geometry spectrum analysis (SGSA), symplectic geometry mode decomposition (SGMD), and symplectic entropy (SymEn), etc. In addition, it also briefly reviews the applications of symplectic geometry on time series analysis, such as the embedding dimension estimation, nonlinear testing, noise reduction, as well as fault diagnosis. Readers who are familiar with the mathematical preliminaries may omit the second section, i.e. the theory part, and go directly to the third section, i.e. the application part.
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Conference papers on the topic "Additive decomposition model"

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Quan, Quan, and Kai-Yuan Cai. "Additive Decomposition and its applications to internal-model-based tracking." In 2009 Joint 48th IEEE Conference on Decision and Control (CDC) and 28th Chinese Control Conference (CCC). IEEE, 2009. http://dx.doi.org/10.1109/cdc.2009.5400007.

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Ghavam, Kamyar, and Reza Naghdabadi. "Corotational Analysis of Elastic-Plastic Hardening Materials Based on Different Kinematic Decompositions." In ASME 2006 Pressure Vessels and Piping/ICPVT-11 Conference. ASMEDC, 2006. http://dx.doi.org/10.1115/pvp2006-icpvt-11-93442.

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In this paper, two corotational modeling for elastic-plastic, mixed hardening materials at finite deformations are introduced. In these models, the additive decomposition of the strain rate tensor as well as the multiplicative decomposition of the deformation gradient tensor is used. For this purpose, corotational constitutive equations are derived for elastic-plastic hardening materials with the non-linear Armstrong-Frederick kinematic hardening and isotropic hardening models. As an application of the proposed constitutive modeling, the governing equations are solved numerically for the simple shear problem with different corotational rates and the stress components are plotted versus the shear displacement. The results for stress, using the additive and the multiplicative decompositions are compared with those obtained experimentally by Ishikawa [1]. This comparison shows a good agreement between the proposed theoretical models and the experimental data. As another example, the Prager kinematic hardening equation is used instead of the Armstrong-Frederick model. In this case the results for stress are compared with the theoretical results of Bruhns et al. [2].
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Chakraborty, Arindam, and Sharif Rahman. "Stochastic Fracture Analysis of Three-Dimensional Functionally Graded Materials Employing Concurrent Multiscale Model." In ASME 2009 Pressure Vessels and Piping Conference. ASMEDC, 2009. http://dx.doi.org/10.1115/pvp2009-78021.

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This article presents a stochastic multiscale fracture analysis of three-dimensional functionally graded, particle-matrix composites with random microstructures employing a moment-modified polynomial dimensional decomposition method. The stochastic model is based on a level-cut, inhomogeneous, filtered Poisson random field for representing spatially-varying random microstructures and a moment-modified polynomial dimensional decomposition for calculating the probabilistic characteristics of crack-driving forces. The decomposition involves Fourier-polynomial expansions of component functions by orthonormal polynomial bases, an additive control variate in conjunction with Monte Carlo simulation for calculating the expansion coefficients, and a moment-modified random output to account for the effects of particle locations and geometry. A numerical problem involving a horizontally placed, planar edge-crack in a three-dimensional functionally graded specimen under a mixed-mode deformation was efficiently calculated by the univariate dimensional decomposition to calculate the statistical moments and distribution functions of crack-driving forces and the conditional probability of fracture initiation. The fracture results show significant variation of the stress intensity factors and fracture initiation probability along the crack front of the fracture specimen.
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4

Mukherjee, Arpan, Rahul Rai, Puneet Singla, Tarunraj Singh, and Abani Patra. "An Adaptive Gaussian Mixture Model Approach Based Framework for Solving Fokker-Planck Kolmogorov Equation Related to High Dimensional Dynamical Systems." In ASME 2016 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/detc2016-60312.

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Engineering systems are often modeled as a large dimensional random process with additive noise. The analysis of such system involves a solution to simultaneous system of Stochastic Differential Equations (SDE). The exact solution to the SDE is given by the evolution of the probability density function (pdf) of the state vector through the application of Stochastic Calculus. The Fokker-Planck-Kolmogorov Equation (FPKE) provides approximate solution to the SDE by giving the time evolution equation for the non-Gaussian pdf of the state vector. In this paper, we outline a computational framework that combines linearization, clustering technique and the Adaptive Gaussian Mixture Model (AGMM) methodology for solving the Fokker-Planck-Kolmogorov Equation (FPKE) related to a high dimensional system. The linearization and clustering technique facilitate easier decomposition of the overall high dimensional FPKE system into a finite number of much lower dimension FPKE systems. The decomposition enables the solution method to be faster. Numerical simulations test the efficacy of our developed framework.
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5

Kulkarni, Shank S., and Tanmay K. Bhandakkar. "Study of the Effect of Large Deformation Through a Finite Deformation Based Constitutive Model for Metallic Glasses." In ASME 2018 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/imece2018-86063.

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A thermodynamically consistent constitutive model of metallic glass is presented by extending the infinitesimal deformation model of Huang et al. [Huang, R., Suo, Z., Prevost, J. H., and Nix,W. D., 2002.Inhomogeneous deformation in metallic glasses,J. Mech. Phys. Solids, 40, 1011–1027] to finite deformation. The underlying theory behind the model is the free volume theory with free volume concentration as the order parameter affected through the processes of diffusion, annihilation and creation. The main assumptions of the model include multiplicative decomposition of deformation gradient and additive decomposition of free energy. The former comprises of elastic, inelastic dilatational component associated with excess free volume concentration and isochoric plastic part while the latter consists of contributions from elastic deformation and free volume concentration. The plastic part evolves according to Mises-theory and the local free volume concentration. Homogeneous simple shear is the model problem solved using the present model and compared with the infinitesimal deformation theory to examine the effect of large deformation on stresses in metallic glasses.
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6

Ghavam, Kamyar, and Reza Naghdabadi. "Elastic-Plastic Modeling of Hardening Materials Using a Corotational Rate Based on the Plastic Spin Tensor." In ASME 2007 Pressure Vessels and Piping Conference. ASMEDC, 2007. http://dx.doi.org/10.1115/pvp2007-26426.

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In this paper based on the multiplicative decomposition of the deformation gradient, the plastic spin tensor and the plastic spin corotational rate are introduced. Using this rate (and also log-rate), an elastic-plastic constitutive model for hardening materials are proposed. In this model, the Armstrong-Frederick kinematic hardening and the isotropic hardening equations are used. The proposed model is solved for the simple shear problem with the material properties of the stainless steel SUS 304. The results are compared with those obtained experimentally by Ishikawa [1]. This comparison shows a good agreement between the results of proposed theoretical model and the experimental data. As another example, the Prager kinematic hardening equation is used. In this case, the stress results are compared with those obtained by Bruhns et al. [2], in which they used the additive decomposition of the strain rate tensor.
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7

Liu, Rui, Meisam Salahshoor, Shreyes N. Melkote, Jayanti Subramaniam, and Troy Marusich. "A Unified Approach to Modeling Material Behavior and Microstructure Evolution in Machining of OFHC Copper." In ASME 2014 International Manufacturing Science and Engineering Conference collocated with the JSME 2014 International Conference on Materials and Processing and the 42nd North American Manufacturing Research Conference. American Society of Mechanical Engineers, 2014. http://dx.doi.org/10.1115/msec2014-4180.

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At a fundamental level, the thermo-mechanical response of metals in dynamic deformation processes such as machining is governed by dislocation processes and associated microstructure evolution. However, the most commonly used material constitutive models in machining are phenomenological (e.g. Johnson-Cook) or semi-phenomenological (e.g. Zerilli-Armstrong) and do not explicitly account for the dependence of material flow stress on dislocation and microstructure evolution processes in a unified manner. The fidelity of machining simulation models is dependent on the amount of micro-scale physics captured in the development of the material constitutive law, microstructure evolution law(s), and the unifying scheme integrating microstructure evolution into the constitutive law. This paper presents a unified material modeling approach that explicitly accounts for dislocation and microstructure evolution processes underlying the finite deformation process. The corresponding evolution laws are formulated and integrated into the constitutive model, which is derived from thermal activation theory and is an additive decomposition of athermal and thermal components of flow stress representing the effects of long-range and short-range obstacles to dislocation motion, respectively. The unified scheme is implemented as a user-defined subroutine in the AdvantEdge™ software (Third Wave Systems LLC) and used to simulate the orthogonal cutting of OFHC copper.
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8

Kaplan, N. H., and I. Erer. "An additive empirical mode decomposition based method for the fusion of remote sensing images." In 2013 6th International Conference on Recent Advances in Space Technologies (RAST). IEEE, 2013. http://dx.doi.org/10.1109/rast.2013.6581193.

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9

Wang, Lei, Mirko Salewski, and Bengt Sunde´n. "Identification and Analysis of Vortical Structures in a Ribbed Channel." In ASME 2008 Fluids Engineering Division Summer Meeting collocated with the Heat Transfer, Energy Sustainability, and 3rd Energy Nanotechnology Conferences. ASMEDC, 2008. http://dx.doi.org/10.1115/fedsm2008-55055.

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Vortical motions, usually called sinews and muscles of fluid motions, constitute important features of turbulent flows and form the base for large-scale transport processes. In this study, we present a variety of flow decomposition techniques to identify and analyze the vortical structures in a ribbed channel. To this end, the instantaneous velocity fields are measured by means of a two-dimensional particle image velocimetry (PIV). Firstly, the implementation of Galilean-, Reynolds- and large-eddy simulation (LES) decompositions on the instantaneous flow fields allows one to perceive the coherent vortices embedded in the separated shear layer. In addition, the proper orthogonal decomposition (POD) is employed to extract the underlying flow features out of the fluctuating velocity and vorticity fields, respectively. For velocity-based decomposition, the first two POD modes show that the shear layer is highly unstable and associated with the ‘flapping’ motion. For vorticity-based decomposition, the first two POD modes are characterized by the distinct horizontal bands which manifest the coherent structures in the shear layer. In order to interpret the flow structures in a convenient way, a linear combination of POD modes (reconstruction) is also carried out in the present study. The result shows that a large-scale, pronounced vortex is recognizable in the region downstream of rib.
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10

Naghdabadi, Reza, and Kamyar Ghavam. "Elastic-Plastic Modeling of the Hardening Materials Based on an Eulerian Strain Tensor and a Proper Corotational Rate." In ASME 2005 Pressure Vessels and Piping Conference. ASMEDC, 2005. http://dx.doi.org/10.1115/pvp2005-71445.

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In this paper a model for analyzing elastic-plastic kinematic hardening materials is introduced, based on the additive decomposition of the corotational rate of an Eulerian strain tensor In this model, the elastic constitutive equation as well as the flow rule and the hardening equation is expressed in terms of the elastic and plastic parts of the corotational rate of the mentioned Eulerian stain tensor and its conjugate stress tensor. In the flow rule, the plastic part of the corotational rate of the Eulerian strain tensor is related to the difference of the deviatoric part of the conjugate stress and the back stress tensors. A proportionality factor is used in this flow rule which must be obtained from a consistency condition based on the von Mises yield criterion. A Prager type kinematic hardening model is used which relates the corotational rate of the back stress tensor to the plastic part of the corotational rate of the Eulerian strain tensor. Also in this paper a proper corotational rate corresponding to the Eulerian strain tensor is introduced. Finally the governing equations for the analysis of elastic-plastic kinematic hardening materials are obtained. As an application, these governing equations are solved numerically for the simple shear problem and the stress and back stress components are plotted versus the shear displacement. The results are compared with those, which are available in the literature.
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