Relevant bibliographies by topics / High-order modeling

Academic literature on the topic 'High-order modeling'

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Published: 14 March 2023

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Journal articles on the topic "High-order modeling"

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Chang, Yuan Lung. "Inferring Markov Chain for Modeling Order Book Dynamics in High Frequency Environment." International Journal of Machine Learning and Computing 5, no. 3 (June 2015): 247–51. http://dx.doi.org/10.7763/ijmlc.2015.v5.515.

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Newman, Christopher, Geoff Womeldorff, Luis Chacón, and Dana A. Knoll. "High-Order/Low-Order Methods for Ocean Modeling." Procedia Computer Science 51 (2015): 2086–96. http://dx.doi.org/10.1016/j.procs.2015.05.477.

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Qing Yang, Qing Yang, Ning Li Qing Yang, Shiyan Hu Ning Li, Heyong Li Shiyan Hu, and Jingwei Zhang Heyong Li. "Click-Through Rate Prediction Algorithm Based on Modeling of Implicit High-Order Feature Importance." 網際網路技術學刊 23, no. 5 (September 2022): 1077–86. http://dx.doi.org/10.53106/160792642022092305016.

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<p>Click-through rate (CTR) prediction plays a central role in online advertising and recommendation systems. In recent years, with the successful application of deep neural networks (DNNs) in many fields, researchers have integrated deep learning into CTR prediction algorithms to model implicit high-order features. However, most of these existing methods unify the weights of implicit higher-order features to predict user behaviors. The importance of such features of different dimensions for predicting user click behaviors are different. Base on this, we propose a prediction method that dynamically learns the importance of implicit high-order features. Specifically, we integrate the output features of deep and shallow components, and adaptively learn the weights of implicit high-order features from among all features through the designed attention network, which effectively capturing the deep interests of users. In addition, this framework has strong versatility and can be combined with shallow models such as Logistic Regression (LR) and Factorization Machines (FMs) to form different models and achieve optimal performance. The extended experiment is conducted on two large-scale datasets, AVAZU and SafeDrive, and the experimental results show that the performance of the proposed model is superior to that of existing baseline models.</p> <p>&nbsp;</p>
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Chen, Jing-Bo. "High-order time discretizations in seismic modeling." GEOPHYSICS 72, no. 5 (September 2007): SM115—SM122. http://dx.doi.org/10.1190/1.2750424.

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Seismic modeling plays an important role in explor-ation geophysics. High-order modeling schemes are in demand for practical reasons. In this context, I present three kinds of high-order time discretizations: Lax-Wendroff methods, Nyström methods, and splitting methods. Lax-Wendroff methods are based on the Taylor expansion and the replacement of high-order temporal derivatives by spatial derivatives, Nyström methods are simplified Runge-Kutta algorithms, and splitting methods comprise substeps for one-step computation. Based on these methods, three schemes with third-order and fourth-order accuracy in time and pseudospectral discretizations in space are presented. I also compare their accuracy, stability, and computational complexity, and discuss advantages and shortcomings of these algorithms. Numerical experiments show that the fourth-order Lax-Wendroff scheme is more efficient for short-time simulations while the fourth-order Nyström scheme and the third-order splitting scheme are more efficient for long-term computations.
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Gavva, S. P. "Modeling of High-Order Overtone Molecular Vibrations." Russian Physics Journal 48, no. 3 (March 2005): 275–79. http://dx.doi.org/10.1007/s11182-005-0119-9.

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Takeuchi, Ichiro, Kazuya Nakagawa, and Koji Tsuda. "Machine Learning Algorithm for High-Order Interaction Modeling." Journal of the Robotics Society of Japan 35, no. 3 (2017): 215–20. http://dx.doi.org/10.7210/jrsj.35.215.

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Dorf, M., M. Dorr, J. Hittinger, W. Lee, and D. Ghosh. "High-order finite-volume modeling of drift waves." Journal of Computational Physics 373 (November 2018): 446–54. http://dx.doi.org/10.1016/j.jcp.2018.07.009.

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Hestholm, Stig. "Acoustic VTI modeling using high-order finite differences." GEOPHYSICS 74, no. 5 (September 2009): T67—T73. http://dx.doi.org/10.1190/1.3157242.

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Two second-order wave equations for acoustic vertical transversely isotropic (VTI) media are transformed to six first-order coupled partial differential equations for a more straighforward numerical implementation of the derivatives. The resulting first-order equations have a more natural form for discretization by any finite-difference, pseudospectral, or finite-element method. I discretized the new equations by high-order finite differences and used synthetic seismograms and snapshots for anisotropic and isotropic cases. The relative merits of placing the source deep and close to a free surface are assessed, illustrating advantages of exciting the source inside or outside of a near-surface, thin, isotropic layer. Results show that traveltimes from deep seismic reflectors can remain virtually unaffected when near-surface isotropic layers are included in acoustic VTI media.
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Tsai, Hsing-Chih. "Modeling concrete strength with high-order neural networks." Neural Computing and Applications 27, no. 8 (August 26, 2015): 2465–73. http://dx.doi.org/10.1007/s00521-015-2017-6.

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Huang, Kai, Vadim Backman, and Igal Szleifer. "Modeling High-Order Chromatin Structure in Single Cells." Biophysical Journal 118, no. 3 (February 2020): 550a—551a. http://dx.doi.org/10.1016/j.bpj.2019.11.3010.

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Dissertations / Theses on the topic "High-order modeling"

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Charous, Aaron( Aaron Solomon). "High-order retractions for reduced-order modeling and uncertainty quantification." Thesis, Massachusetts Institute of Technology, 2006. https://hdl.handle.net/1721.1/130904.

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Thesis: S.M., Massachusetts Institute of Technology, Center for Computational Science & Engineering, February, 2021
Cataloged from the official PDF version of thesis.
Includes bibliographical references (pages 145-151).
Though computing power continues to grow quickly, our appetite to solve larger and larger problems grows just as fast. As a consequence, reduced-order modeling has become an essential technique in the computational scientist's toolbox. By reducing the dimensionality of a system, we are able to obtain approximate solutions to otherwise intractable problems. And because the methodology we develop is sufficiently general, we may agnostically apply it to a plethora of problems, whether the high dimensionality arises due to the sheer size of the computational domain, the fine resolution we require, or stochasticity of the dynamics. In this thesis, we develop time integration schemes, called retractions, to efficiently evolve the dynamics of a system's low-rank approximation. Through the study of differential geometry, we are able to analyze the error incurred at each time step. A novel, explicit, computationally inexpensive set of algorithms, which we call perturbative retractions, are proposed that converge to an ideal retraction that projects exactly to the manifold of fixed-rank matrices. Furthermore, each perturbative retraction itself exhibits high-order convergence to the best low-rank approximation of the full-rank solution. We show that these high-order retractions significantly reduce the numerical error incurred over time when compared to a naive Euler forward retraction. Through test cases, we demonstrate their efficacy in the cases of matrix addition, real-time data compression, and deterministic and stochastic differential equations.
by Aaron Charous.
S.M.
S.M. Massachusetts Institute of Technology, Center for Computational Science & Engineering
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Charous, Aaron (Aaron Solomon). "High-order retractions for reduced-order modeling and uncertainty quantification." Thesis, Massachusetts Institute of Technology, 2021. https://hdl.handle.net/1721.1/130904.

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Abstract:
Thesis: S.M., Massachusetts Institute of Technology, Center for Computational Science & Engineering, February, 2021
Cataloged from the official PDF version of thesis.
Includes bibliographical references (pages 145-151).
Though computing power continues to grow quickly, our appetite to solve larger and larger problems grows just as fast. As a consequence, reduced-order modeling has become an essential technique in the computational scientist's toolbox. By reducing the dimensionality of a system, we are able to obtain approximate solutions to otherwise intractable problems. And because the methodology we develop is sufficiently general, we may agnostically apply it to a plethora of problems, whether the high dimensionality arises due to the sheer size of the computational domain, the fine resolution we require, or stochasticity of the dynamics. In this thesis, we develop time integration schemes, called retractions, to efficiently evolve the dynamics of a system's low-rank approximation. Through the study of differential geometry, we are able to analyze the error incurred at each time step. A novel, explicit, computationally inexpensive set of algorithms, which we call perturbative retractions, are proposed that converge to an ideal retraction that projects exactly to the manifold of fixed-rank matrices. Furthermore, each perturbative retraction itself exhibits high-order convergence to the best low-rank approximation of the full-rank solution. We show that these high-order retractions significantly reduce the numerical error incurred over time when compared to a naive Euler forward retraction. Through test cases, we demonstrate their efficacy in the cases of matrix addition, real-time data compression, and deterministic and stochastic differential equations.
by Aaron Charous.
S.M.
S.M. Massachusetts Institute of Technology, Center for Computational Science & Engineering
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Velechovsky, Jan. "High-order numerical methods for laser plasma modeling." Thesis, Bordeaux, 2015. http://www.theses.fr/2015BORD0098/document.

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Cette thèse présente le développement d’une méthode ALE pour la modélisation del’interaction laser–plasma. La particularité de cette méthode est l’utilisation d’une étape de projectiond’ordre élevé. Cette étape de projection consiste en une interpolation conservative des quantitésconservatives du maillage Lagrangien sur un maillage régularisé. Afin d’éviter les oscillationsnumériques non-physiques, les flux numériques d’ordre élevé sont combinés avec des fluxnumériques d’ordre moins élevé. Ces flux numériques sont obtenu en considérant les quantitésconservatives constantes par morceaux. Cette méthode pour la discrétisation cellule–centrée consisteà préserver les maximums locaux pour la densité, la vitesse et l’énergie interne. Aspects particuliersde la méthode sont appliquées pour la projection la quantité de mouvement pour la discrétisation’staggered’. Nous l’utilisons ici dans le cadre de la projection sous la forme de la méthode FluxCorrection Remapping (FCR). Dans cette thèse le volet applicatif concerne la modélisation del’interaction d’un laser énergétique avec de plasma et des matériaux microstructures. Un intérêtparticulier est porté à la modélisation de l’absorption du laser par une mousse de faible densité.L’absorption se fait à deux échelles spatiales simultanément. Ce modèle d’absorption laser à deuxéchelles est mis en oeuvre dans le code PALE hydrodynamique. Les simulations numériques de lavitesse de pénétration du laser dans une mousse à faible densité sont en bon accord avec lesdonnées expérimentales
This thesis presents the overview and the original contributions to a high–orderArbitrary Lagrangian–Eulerian (ALE) method applicable for the laser–generated plasma modeling withthe focus to a remapping step of the ALE method. The remap is the conservative interpolation of theconservative quantities from a low–quality Lagrangian grid onto a better, smoothed one. To avoidnon–physical numerical oscillations, the high–order numerical fluxes of the reconstruction arecombined with the low–order (first–order) numerical fluxes produced by a standard donor remappingmethod. The proposed method for a cell–centered discretization preserves bounds for the density,velocity and specific internal energy by its construction. Particular symmetry–preserving aspects of themethod are applied for a staggered momentum remap. The application part of the thesis is devoted tothe laser radiation absorption modeling in plasmas and microstructures materials with the particularinterest in the laser absorption in low–density foams. The absorption is modeled on two spatial scalessimultaneously. This two–scale laser absorption model is implemented in the hydrodynamic codePALE. The numerical simulations of the velocity of laser penetration in a low–density foam are in agood agreement with the experimental data
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Heidkamp, Holger [Verfasser]. "Modeling Localization and Failure with High-Order Finite Elements / Holger Heidkamp." Aachen : Shaker, 2008. http://d-nb.info/1164341642/34.

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Beisiegel, Nicole [Verfasser], and Jörn [Akademischer Betreuer] Behrens. "High-order Adaptive Discontinuous Galerkin Inundation Modeling / Nicole Beisiegel. Betreuer: Jörn Behrens." Hamburg : Staats- und Universitätsbibliothek Hamburg, 2014. http://d-nb.info/1060484749/34.

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Beisiegel, Nicole Verfasser], and Jörn [Akademischer Betreuer] [Behrens. "High-order Adaptive Discontinuous Galerkin Inundation Modeling / Nicole Beisiegel. Betreuer: Jörn Behrens." Hamburg : Staats- und Universitätsbibliothek Hamburg, 2014. http://nbn-resolving.de/urn:nbn:de:gbv:18-70360.

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Tong, Oisin. "Development of a Three-Dimensional High-Order Strand-Grids Approach." DigitalCommons@USU, 2016. https://digitalcommons.usu.edu/etd/4711.

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Development of a novel high-order flux correction method on strand grids is presented. The method uses a combination of flux correction in the unstructured plane and summation-by-parts operators in the strand direction to achieve high-fidelity solutions. Low-order truncation errors are cancelled with accurate flux and solution gradients in the flux correction method, thereby achieving a formal order of accuracy of 3, although higher orders are often obtained, especially for highly viscous flows. In this work, the scheme is extended to high-Reynolds number computations in both two and three dimensions. Turbulence closure is achieved with a robust version of the Spalart-Allmaras turbulence model that accommodates negative values of the turbulence working variable, and the Menter SST turbulence model, which blends the k-ε and k-ω turbulence models for better accuracy. A major advantage of this high-order formulation is the ability to implement traditional finite volume-like limiters to cleanly capture shocked and discontinuous flow. In this work, this approach is explored via a symmetric limited positive (SLIP) limiter. Extensive verification and validation is conducted in two and three dimensions to determine the accuracy and fidelity of the scheme for a number of different cases. Verification studies show that the scheme achieves better than third order accuracy for low and high-Reynolds number flow. Cost studies show that in three-dimensions, the third-order flux correction scheme requires only 30% more walltime than a traditional second-order scheme on strand grids to achieve the same level of convergence. In order to overcome meshing issues at sharp corners and other small-scale features, a unique approach to traditional geometry, coined "asymptotic geometry," is explored. Asymptotic geometry is achieved by filtering out small-scale features in a level set domain through min/max flow. This approach is combined with a curvature based strand shortening strategy in order to qualitatively improve strand grid mesh quality.
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Ye, Fei. "Developing Efficient High-Order Transport Schemes for Cross-Scale Coupled Estuary-Ocean Modeling." W&M ScholarWorks, 2017. https://scholarworks.wm.edu/etd/1516639591.

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Geophysical fluid dynamics (GFD) models have progressed greatly in simulating the world’s oceans and estuaries in the past three decades, thanks to the development of novel numerical algorithms and the advent of massively parallel high-performance computing platforms. Study of inter-related processes on multi-scales (e.g., between large-scale (remote) processes and small-scale (local) processes) has always been an important theme for GFD modeling. For this purpose, models based on unstructured-grid (UG) have shown great potential because of their superior abilities in enabling multi-resolution and in fitting geometry and boundary. Despite UG models’ successful applications on coastal systems, significant obstacles still exist that have so far prevented UG models from realizing their full cross-scale capability. The pressing issues include the computation overhead resulting from large contrasts in the spatial resolutions, and the relative lack of skill for UG model in the eddying regime. Specifically for our own implicit UG model (SCHISM), the transport solver often emerges as a major bottleneck for both accuracy and efficiency. The overall goal of this dissertation is two-fold. The first goal is to address the challenges in tracer transport by developing efficient high-order schemes for the transport processes and test them in the framework of a community supported modeling system (SCHISM: Semi-implicit Cross-scale Hydroscience Integrated System Model) for cross-scale processes. The second goal is to utilize the new schemes developed in this dissertation and elsewhere to build a bona fide cross-scale Chesapeake Bay model and use it to address some key knowledge gaps in the physical processes in this system and to better assist decision makers of coastal resource management. The work on numerical scheme development has resulted in two new high-order transport solvers. The first solver tackles the vertical transport that often imposes the most stringent constraint on model efficiency (Chapter 2). With an implicit method and two flux limiters in both space and time, the new TVD2 solver leads to a speed-up of 1.6-6.0 in various cross-scale applications as compared to traditional explicit methods, while achieving 2nd-order accuracy in both space and time. Together with a flexible vertical gridding system, the flow over steep slopes can be faithfully simulated efficiently and accurately without altering the underlying bathymetry. The second scheme aims at improving the model skill in the eddying ocean (Chapter 4). UG coastal models tend to under-resolve features like meso-scale eddies and meanders, and this issue is partially attributed to the numerical diffusion in the transport schemes that are originally developed for estuarine applications. to address this issue, a 3rd-order transport scheme based on WENO formulation is developed, and is demonstrated to improve the meso-scale features. The new solvers are then tested in the Chesapeake Bay and adjacent Atlantic Ocean on small, medium and large domains respectively, corresponding to the three main chapters of this dissertation (Chapter 2-4), with an ultimate goal of achieving a seamless cross-scale model from the Gulf Stream to the shallow regions in the Bay tributaries and sub-tributaries. We highlight the dominant role played by the bathymetry in nearshore systems and the detrimental effects of bathymetric smoothing commonly used in many coastal models (Chapter 3). With the new methods developed in this dissertation and elsewhere, the model has enabled the analyses on some important processes that are hard to quantify with traditional techniques, e.g., the effect of channel-shoal contrast on lateral circulation and salinity distribution, hypoxia volume, the influence of realistic bathymetry on the freshwater plume etc. Potential topics for future research are also discussed at the end. In addition, the new solvers have also been successfully exported to many other oceanic and nearshore systems around the world via user groups of our community modeling system (cf. ‘Publications’ under ‘schism.wiki’).
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Collins, Justin A. Valentine Jerry. "Higher-order thinking in the high-stakes accountability era linking student engagement and test performance /." Diss., Columbia, Mo. : University of Missouri-Columbia, 2009. http://hdl.handle.net/10355/6769.

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The entire thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file; a non-technical public abstract appears in the public.pdf file. Title from PDF of title page (University of Missouri--Columbia, viewed on March 25, 2010). Thesis advisor: Dr. Jerry W. Valentine. Vita. Includes bibliographical references.
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Powers, Sean W. "Analysis of Stresses in Metal Sheathed Thermocouples in High-Temperature, Hypersonic Flows." Thesis, Virginia Tech, 2020. http://hdl.handle.net/10919/98000.

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Flow temperature sensing remains important for many hypersonic aerodynamics and propulsion applications. Flight test applications, in particular, demand robust and accurate sensing, making thermocouple sensors attractive. Even for these extremely well-developed sensors, the prediction of stresses (hoop, radial, and axial) within thermocouple sheaths for custom-configured probes remains a topic of great concern for ensuring adequate lifetime of sensors. In contemporary practice, high-fidelity simulations must be run to prove if a new design will work at all, albeit at significant time and expense. Given the time and money it takes to run high-fidelity simulations, rapid optimization of sensor configurations is often impossible, or at a minimum, impractical. The developments presented in this Thesis address the need for hypersonic flow temperature sensor structural predictions which are compatible with rapid design iteration. The derivation and implementation of a new analytical, low-order model to predict stresses (hoop, radial, and axial) within the sheath of a thermocouple are provided. The analytical model is compared to high-fidelity ANSYS mechanical simulations as well as simplified experimental data. The predictions using the newly developed structural low-order model are in excellent agreement with the numerically simulated results and experimental results with an absolute maximum percent error of approximately 4% and 9.5%, respectively, thus validating the model. A MATLAB GUI composed of the combination of a thermal low-order model outlined in additional references [1] through [6] and the new structural low-order model for thermocouples was developed. This code is capable of solving a highly generalized version of the 1-D pin fin equation, allowing for the solution of the temperature distribution in a sensor taking into account conduction, convection, and radiation heat transfer which is not possible with other existing analytical solutions. This temperature distribution is then used in the analytical structural low-order model. This combination allows for the thermal and structural performance of a thermocouple to be found analytically and compared quickly with other designs.
M.S.
Thermocouples are a device for measuring temperature, consisting of two wires of different metals connected at two different points. This configuration produces a temperature-dependent voltage as a result of the thermoelectric effect. Preexisting curves are used to relate the voltage to temperature. Thermocouples are extensively used in high-temperature high-stress environments such as in rockets, jet engines, or any high-corrosive environment. Accurately predicting the stresses within the sheath of a metal-clad thermocouple in extreme conditions is required for many research areas including hypersonic aerodynamics and various propulsion applications. Even for these extremely well-developed and widely used sensors, the accurate prediction of stresses within the metal sheath remains a topic of great concern for ensuring the sensor’s survivability in these extreme conditions. Current engineering practice is to use high-fidelity numerical simulations (Finite Element Analysis) to predict the stresses within the sheath. Perhaps the biggest drawback to this approach is the time it takes to model, mesh, and set-up these simulations. Comparative studies between different designs using numerical simulations are almost impossible due to the time requirement. This Thesis will present an analytically derived quasi-3D solution to find the stresses within the sheath. These equations were implemented into a low-order model that can handle varying temperature, geometry, and material inputs. This model was validated against both high-fidelity numerical simulations (ANSYS Mechanical) and a simplified experiment. The predictions using this newly developed structural low-order model are in excellent agreement with the numerically simulated results and experimental results.
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Books on the topic "High-order modeling"

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Thomas, Gregory Robert. A combined high-order spectral and boundary integral equation method for modelling wave interactions with submerged bodies. Springfield, Va: Available from National Technical Information Service, 1996.

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Habib, Ammari, Capdeboscq Yves 1971-, and Kang Hyeonbae, eds. Multi-scale and high-contrast PDE: From modelling, to mathematical analysis, to inversion : Conference on Multi-scale and High-contrast PDE:from Modelling, to Mathematical Analysis, to Inversion, June 28-July 1, 2011, University of Oxford, United Kingdom. Providence, R.I: American Mathematical Society, 2010.

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Reduced Order Modeling For High Speed Flows with Moving Shocks. Storming Media, 2001.

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Abgrall, Rémi, Pietro Marco Congedo, Cécile Dobrzynski, Héloïse Beaugendre, and Vincent Perrier. High Order Nonlinear Numerical Schemes for Evolutionary PDEs: Proceedings of the European Workshop HONOM 2013, Bordeaux, France, March 18-22 2013. Springer London, Limited, 2014.

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High Order Nonlinear Numerical Schemes for Evolutionary PDEs: Proceedings of the European Workshop HONOM 2013, Bordeaux, France, March 18-22 2013. Springer, 2014.

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Mauranen, Anna. Second-Order Language Contact. Edited by Markku Filppula, Juhani Klemola, and Devyani Sharma. Oxford University Press, 2014. http://dx.doi.org/10.1093/oxfordhb/9780199777716.013.010.

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This chapter discusses the nature of English as a lingua franca (ELF) as uniquely complex ‘second order language contact’, which arises from contact between ‘similects’ of speakers from given first language backgrounds. The data is drawn from speech in academic communities. ELF is best understood as operating on three levels: the macro-social, the micro-social, and the cognitive. English as a lingua franca is largely similar to English as a native language in comparable social circumstances, but it also manifests lexico-grammatical features that are clearly different: nonstandard grammatical and lexical forms are relatively common, together with lexical simplification in a statistical sense. As speakers make competent use of discourse phenomena for communicative success, it seems that lexico-grammatical accuracy may be less crucial to communication. The findings lend support to modelling language processes as discourse-driven, fuzzy and approximate, with a high level of tolerance for variability in form.
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Shaikh, Mohd Faraz. Machine Learning in Detecting Auditory Sequences in Magnetoencephalography Data : Research Project in Computational Modelling and Simulation. Technische Universität Dresden, 2021. http://dx.doi.org/10.25368/2022.411.

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Does your brain replay your recent life experiences while you are resting? An open question in neuroscience is which events does our brain replay and is there any correlation between the replay and duration of the event? In this study I tried to investigate this question by using Magnetoencephalography data from an active listening experiment. Magnetoencephalography (MEG) is a non-invasive neuroimaging technique used to study the brain activity and understand brain dynamics in perception and cognitive tasks particularly in the fields of speech and hearing. It records the magnetic field generated in our brains to detect the brain activity. I build a machine learning pipeline which uses part of the experiment data to learn the sound patterns and then predicts the presence of sound in the later part of the recordings in which the participants were made to sit idle and no sound was fed. The aim of the study of test replay of learned sound sequences in the post listening period. I have used classification scheme to identify patterns if MEG responses to different sound sequences in the post task period. The study concluded that the sound sequences can be identified and distinguished above theoretical chance level and hence proved the validity of our classifier. Further, the classifier could predict the sound sequences in the post-listening period with very high probability but in order to validate the model results on post listening period, more evidence is needed.
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Book chapters on the topic "High-order modeling"

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Givoli, Dan. "Non-Reflecting Boundaries: High-Order Treatment." In A Celebration of Mathematical Modeling, 53–72. Dordrecht: Springer Netherlands, 2004. http://dx.doi.org/10.1007/978-94-017-0427-4_4.

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Bottacchi, Stefano. "Theory and Modeling of Complex Optical Modulations." In Handbook of High-Order Optical Modulations, 331–573. New York, NY: Springer New York, 2021. http://dx.doi.org/10.1007/978-1-0716-1195-1_4.

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Bottacchi, Stefano. "Statistical Modeling of PAM Signals and Power Spectra." In Handbook of High-Order Optical Modulations, 203–329. New York, NY: Springer New York, 2021. http://dx.doi.org/10.1007/978-1-0716-1195-1_3.

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Anastassiou, George A., and Oktay Duman. "High Order Statistical Fuzzy Korovkin-Type Approximation Theory." In Towards Intelligent Modeling: Statistical Approximation Theory, 199–206. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-19826-7_16.

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Guillamet, David, Baback Moghaddam, and Jordi Vitrià. "Modeling High-Order Dependencies in Local Appearance Models." In Pattern Recognition and Image Analysis, 308–16. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-540-44871-6_36.

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Kim, Byung-soo, Min Sun, Pushmeet Kohli, and Silvio Savarese. "Relating Things and Stuff by High-Order Potential Modeling." In Computer Vision – ECCV 2012. Workshops and Demonstrations, 293–304. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-33885-4_30.

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St.-Cyr, Amik, and Stephen J. Thomas. "High-Order Finite Element Methods for Parallel Atmospheric Modeling." In Lecture Notes in Computer Science, 256–62. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11428831_32.

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Cheng, Yi-Chung, and Sheng-Tun Li. "A Best-Match Forecasting Model for High-Order Fuzzy Time Series." In Time Series Analysis, Modeling and Applications, 331–45. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-33439-9_15.

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Armenta, Roberto B., and Costas D. Sarris. "Boundary Modeling and High-Order Convergence in Finite-Difference Methods." In Computational Electromagnetics—Retrospective and Outlook, 225–43. Singapore: Springer Singapore, 2014. http://dx.doi.org/10.1007/978-981-287-095-7_9.

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Wang, Pan. "Finite-Time Stability Analysis of Fractional-Order High-Order Hopfield Neural Networks with Delays." In Theory, Methodology, Tools and Applications for Modeling and Simulation of Complex Systems, 121–30. Singapore: Springer Singapore, 2016. http://dx.doi.org/10.1007/978-981-10-2672-0_13.

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Conference papers on the topic "High-order modeling"

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Zahr, M. "High-Order Implicit Shock Tracking." In 10th International Conference on Adaptative Modeling and Simulation. CIMNE, 2021. http://dx.doi.org/10.23967/admos.2021.047.

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Kazakov, Vasily I., Oleg D. Moskaletz, and Mikhail A. Vaganov. "High-order transmissive diffraction grating for high-resolution spectral systems." In Modeling Aspects in Optical Metrology VII, edited by Bernd Bodermann, Karsten Frenner, and Richard M. Silver. SPIE, 2019. http://dx.doi.org/10.1117/12.2526004.

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Johnson, Olin. "High order finite-difference modeling on supercomputers." In 1985 SEG Technical Program Expanded Abstracts. SEG, 1985. http://dx.doi.org/10.1190/1.1892865.

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Wang, Qi, Li-xin Wang, and Qiang Shen. "Modeling strategy of high order ARMA model." In 2016 IEEE Chinese Guidance, Navigation and Control Conference (CGNCC). IEEE, 2016. http://dx.doi.org/10.1109/cgncc.2016.7829097.

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Shumlak, U., J. B. Coughlin, D. W. Crews, I. A. M. Datta, A. Ho, A. R. Johansen, E. T. Meier, Y. Takagaki, and W. R. Thomas. "High-Order Finite Element Method for High-Fidelity Plasma Modeling." In 2020 IEEE International Conference on Plasma Science (ICOPS). IEEE, 2020. http://dx.doi.org/10.1109/icops37625.2020.9717941.

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Crabill, Jacob A., Jayanarayanan Sitaraman, and Antony Jameson. "A High-Order Overset Method on Moving and Deforming Grids." In AIAA Modeling and Simulation Technologies Conference. Reston, Virginia: American Institute of Aeronautics and Astronautics, 2016. http://dx.doi.org/10.2514/6.2016-3225.

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Sai, Ryuichi, John Mellor-Crummey, Xiaozhu Meng, Mauricio Araya-Polo, and Jie Meng. "Accelerating High-Order Stencils on GPUs." In 2020 IEEE/ACM Performance Modeling, Benchmarking and Simulation of High Performance Computer Systems (PMBS). IEEE, 2020. http://dx.doi.org/10.1109/pmbs51919.2020.00014.

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Shumlak, U., R. Lilly, S. Miller, N. Reddell, and E. Sousa. "High-order finite element method for plasma modeling." In 2013 IEEE 40th International Conference on Plasma Sciences (ICOPS). IEEE, 2013. http://dx.doi.org/10.1109/plasma.2013.6634927.

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Friedrich, L., M. Curti, B. Gysen, J. Jansen, and E. Lomonova. "High-order methods applied to electrical machine modeling." In 2018 IEEE International Magnetic Conference (INTERMAG). IEEE, 2018. http://dx.doi.org/10.1109/intmag.2018.8508189.

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Poggie, Jonathan. "High-Order Numerical Methods for Electrical Discharge Modeling." In 41st Plasmadynamics and Lasers Conference. Reston, Virigina: American Institute of Aeronautics and Astronautics, 2010. http://dx.doi.org/10.2514/6.2010-4632.

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Reports on the topic "High-order modeling"

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Parish, Eric. Multiscale modeling high-order methods and data-driven modeling. Office of Scientific and Technical Information (OSTI), October 2020. http://dx.doi.org/10.2172/1673827.

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Mavriplis, Dimitri J. High-Order Modeling of Applied Multi-Physics Phenomena. Fort Belvoir, VA: Defense Technical Information Center, September 2009. http://dx.doi.org/10.21236/ada513855.

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Beattie, Christopher A., Jeffrey T. Borggaard, Serkan Gugercin, and Traian Iliescu. High Performance Parallel Algorithms for Improved Reduced-Order Modeling. Fort Belvoir, VA: Defense Technical Information Center, May 2008. http://dx.doi.org/10.21236/ada483934.

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Carlberg, Kevin, Micah Howard, and Brian Freno. Rapid high-fidelity aerothermal responses with quantified uncertainties via reduced-order modeling. Office of Scientific and Technical Information (OSTI), August 2018. http://dx.doi.org/10.2172/1464878.

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Krispin, Jacob, Mark Potts, Brady Brown, Ralph Ferguson, and James Collins. High-Order Godunov Schemes for Multiphase Gas-Particulate Flowfield Modeling and Simulation. Fort Belvoir, VA: Defense Technical Information Center, September 2000. http://dx.doi.org/10.21236/ada385335.

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Povitsky, A., and H. Gopalan. Modeling of Flow about Pitching and Plunging Airfoil Using High-Order Schemes. Fort Belvoir, VA: Defense Technical Information Center, March 2008. http://dx.doi.org/10.21236/ada478589.

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Zhang, Guannan, Clayton G. Webster, and Max D. Gunzburger. An adaptive sparse-grid high-order stochastic collocation method for Bayesian inference in groundwater reactive transport modeling. Office of Scientific and Technical Information (OSTI), September 2012. http://dx.doi.org/10.2172/1055118.

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Heitman, Joshua L., Alon Ben-Gal, Thomas J. Sauer, Nurit Agam, and John Havlin. Separating Components of Evapotranspiration to Improve Efficiency in Vineyard Water Management. United States Department of Agriculture, March 2014. http://dx.doi.org/10.32747/2014.7594386.bard.

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Vineyards are found on six of seven continents, producing a crop of high economic value with much historic and cultural significance. Because of the wide range of conditions under which grapes are grown, management approaches are highly varied and must be adapted to local climatic constraints. Research has been conducted in the traditionally prominent grape growing regions of Europe, Australia, and the western USA, but far less information is available to guide production under more extreme growing conditions. The overarching goal of this project was to improve understanding of vineyard water management related to the critical inter-row zone. Experiments were conducted in moist temperate (North Carolina, USA) and arid (Negev, Israel) regions in order to address inter-row water use under high and low water availability conditions. Specific objectives were to: i) calibrate and verify a modeling technique to identify components of evapotranspiration (ET) in temperate and semiarid vineyard systems, ii) evaluate and refine strategies for excess water removal in vineyards for moist temperate regions of the Southeastern USA, and iii) evaluate and refine strategies for water conservation in vineyards for semi-arid regions of Israel. Several new measurement and modeling techniques were adapted and assessed in order to partition ET between favorable transpiration by the grapes and potentially detrimental water use within the vineyard inter-row. A micro Bowen ratio measurement system was developed to quantify ET from inter-rows. The approach was successful at the NC site, providing strong correlation with standard measurement approaches and adding capability for continuous, non-destructive measurement within a relatively small footprint. The environmental conditions in the Negev site were found to limit the applicability of the technique. Technical issues are yet to be solved to make this technique sufficiently robust. The HYDRUS 2D/3D modeling package was also adapted using data obtained in a series of intense field campaigns at the Negev site. The adapted model was able to account for spatial variation in surface boundary conditions, created by diurnal canopy shading, in order to accurately calculate the contribution of interrow evaporation (E) as a component of system ET. Experiments evaluated common practices in the southeastern USA: inter-row cover crops purported to reduce water availability and thereby favorably reduce grapevine vegetative growth; and southern Israel: drip irrigation applied to produce a high value crop with maximum water use efficiency. Results from the NC site indicated that water use by the cover crop contributed a significant portion of vineyard ET (up to 93% in May), but that with ample rainfall typical to the region, cover crop water use did little to limit water availability for the grape vines. A potential consequence, however, was elevated below canopy humidity owing to the increased inter-row evapotranspiration associated with the cover crops. This creates increased potential for fungal disease occurrence, which is a common problem in the region. Analysis from the Negev site reveals that, on average, E accounts for about10% of the total vineyard ET in an isolated dripirrigated vineyard. The proportion of ET contributed by E increased from May until just before harvest in July, which could be explained primarily by changes in weather conditions. While non-productive water loss as E is relatively small, experiments indicate that further improvements in irrigation efficiency may be possible by considering diurnal shading effects on below canopy potential ET. Overall, research provided both scientific and practical outcomes including new measurement and modeling techniques, and new insights for humid and arid vineyard systems. Research techniques developed through the project will be useful for other agricultural systems, and the successful synergistic cooperation amongst the research team offers opportunity for future collaboration.
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Semerikov, Serhiy, Hanna Kucherova, Vita Los, and Dmytro Ocheretin. Neural Network Analytics and Forecasting the Country's Business Climate in Conditions of the Coronavirus Disease (COVID-19). CEUR Workshop Proceedings, April 2021. http://dx.doi.org/10.31812//123456789/4364.

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The prospects for doing business in countries are also determined by the business confidence index. The purpose of the article is to model trends in indicators that determine the state of the business climate of countries, in particular, the period of influence of the consequences of COVID-19 is of scientific interest. The approach is based on the preliminary results of substantiating a set of indicators and applying the taxonomy method to substantiate an alternative indicator of the business climate, the advantage of which is its advanced nature. The most significant factors influencing the business climate index were identified, in particular, the annual GDP growth rate and the volume of retail sales. The similarity of the trends in the calculated and actual business climate index was obtained, the forecast values were calculated with an accuracy of 89.38%. And also, the obtained modeling results were developed by means of building and using neural networks with learning capabilities, which makes it possible to improve the quality and accuracy of the business climate index forecast up to 96.22%. It has been established that the consequences of the impact of COVID-19 are forecasting a decrease in the level of the country's business climate index in the 3rd quarter of 2020. The proposed approach to modeling the country's business climate is unified, easily applied to the macroeconomic data of various countries, demonstrates a high level of accuracy and quality of forecasting. The prospects for further research are modeling the business climate of the countries of the world in order to compare trends and levels, as well as their changes under the influence of quarantine restrictions.
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Russo, David, Daniel M. Tartakovsky, and Shlomo P. Neuman. Development of Predictive Tools for Contaminant Transport through Variably-Saturated Heterogeneous Composite Porous Formations. United States Department of Agriculture, December 2012. http://dx.doi.org/10.32747/2012.7592658.bard.

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The vadose (unsaturated) zone forms a major hydrologic link between the ground surface and underlying aquifers. To understand properly its role in protecting groundwater from near surface sources of contamination, one must be able to analyze quantitatively water flow and contaminant transport in variably saturated subsurface environments that are highly heterogeneous, often consisting of multiple geologic units and/or high and/or low permeability inclusions. The specific objectives of this research were: (i) to develop efficient and accurate tools for probabilistic delineation of dominant geologic features comprising the vadose zone; (ii) to develop a complementary set of data analysis tools for discerning the fractal properties of hydraulic and transport parameters of highly heterogeneous vadose zone; (iii) to develop and test the associated computational methods for probabilistic analysis of flow and transport in highly heterogeneous subsurface environments; and (iv) to apply the computational framework to design an “optimal” observation network for monitoring and forecasting the fate and migration of contaminant plumes originating from agricultural activities. During the course of the project, we modified the third objective to include additional computational method, based on the notion that the heterogeneous formation can be considered as a mixture of populations of differing spatial structures. Regarding uncertainly analysis, going beyond approaches based on mean and variance of system states, we succeeded to develop probability density function (PDF) solutions enabling one to evaluate probabilities of rare events, required for probabilistic risk assessment. In addition, we developed reduced complexity models for the probabilistic forecasting of infiltration rates in heterogeneous soils during surface runoff and/or flooding events Regarding flow and transport in variably saturated, spatially heterogeneous formations associated with fine- and coarse-textured embedded soils (FTES- and CTES-formations, respectively).We succeeded to develop first-order and numerical frameworks for flow and transport in three-dimensional (3-D), variably saturated, bimodal, heterogeneous formations, with single and dual porosity, respectively. Regarding the sampling problem defined as, how many sampling points are needed, and where to locate them spatially in the horizontal x₂x₃ plane of the field. Based on our computational framework, we succeeded to develop and demonstrate a methdology that might improve considerably our ability to describe quntitaively the response of complicated 3-D flow systems. The results of the project are of theoretical and practical importance; they provided a rigorous framework to modeling water flow and solute transport in a realistic, highly heterogeneous, composite flow system with uncertain properties under-specified by data. Specifically, they: (i) enhanced fundamental understanding of the basic mechanisms of field-scale flow and transport in near-surface geological formations under realistic flow scenarios, (ii) provided a means to assess the ability of existing flow and transport models to handle realistic flow conditions, and (iii) provided a means to assess quantitatively the threats posed to groundwater by contamination from agricultural sources.
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