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Journal articles on the topic 'Componentwise error'

Author: Grafiati

Published: 1 April 2023

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1

Huang, Rong, and Li Zhu. "Componentwise backward error analysis of Neville elimination." Linear Algebra and its Applications 451 (June 2014): 33–48. http://dx.doi.org/10.1016/j.laa.2014.03.014.

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2

Wang, Z., and Y. x. Yuan. "Componentwise error bounds for linear complementarity problems." IMA Journal of Numerical Analysis 31, no. 1 (September 26, 2009): 348–57. http://dx.doi.org/10.1093/imanum/drp026.

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3

Shen, Z., and M. A. Wolfe. "On certain computable tests and componentwise error bounds." Computing 50, no. 4 (December 1993): 353–68. http://dx.doi.org/10.1007/bf02243877.

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4

Voicu, Mihail. "Observing the state with componentwise exponentially decaying error." Systems & Control Letters 9, no. 1 (June 1987): 33–42. http://dx.doi.org/10.1016/0167-6911(87)90006-5.

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5

Arioli, M., H. Munthe-Kaas, and L. Valdettaro. "Componentwise error analysis for FFTs with applications to fast Helmholtz solvers." Numerical Algorithms 12, no. 1 (March 1996): 65–88. http://dx.doi.org/10.1007/bf02141741.

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6

Huang, Rong. "Componentwise error analysis for linear systems associated with sign regular matrices." Journal of Computational and Applied Mathematics 255 (January 2014): 133–41. http://dx.doi.org/10.1016/j.cam.2013.04.045.

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7

Pandian, Maharaja C. "A Convergence Test and Componentwise Error Estimates for Newton Type Methods." SIAM Journal on Numerical Analysis 22, no. 4 (August 1985): 779–91. http://dx.doi.org/10.1137/0722047.

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8

Eisenstat, Stanley C., Serge Gratton, and David Titley-Peloquin. "On the Symmetric Componentwise Relative Backward Error for Linear Systems of Equations." SIAM Journal on Matrix Analysis and Applications 38, no. 4 (January 2017): 1100–1115. http://dx.doi.org/10.1137/140986566.

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9

Huang, Rong. "Componentwise error analysis for the block LU factorization of totally nonnegative matrices." Linear Algebra and its Applications 439, no. 10 (November 2013): 2888–900. http://dx.doi.org/10.1016/j.laa.2013.08.019.

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10

Rump, Siegfried M. "Improved componentwise verified error bounds for least squares problems and underdetermined linear systems." Numerical Algorithms 66, no. 2 (July 11, 2013): 309–22. http://dx.doi.org/10.1007/s11075-013-9735-6.

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11

Stolwijk, Jeroen J., and Volker Mehrmann. "Error Analysis and Model Adaptivity for Flows in Gas Networks." Analele Universitatii "Ovidius" Constanta - Seria Matematica 26, no. 2 (July 1, 2018): 231–66. http://dx.doi.org/10.2478/auom-2018-0027.

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Abstract In the simulation and optimization of natural gas flow in a pipeline network, a hierarchy of models is used that employs different formulations of the Euler equations. While the optimization is performed on piecewise linear models, the flow simulation is based on the one to three dimensional Euler equations including the temperature distributions. To decide which model class in the hierarchy is adequate to achieve a desired accuracy, this paper presents an error and perturbation analysis for a two level model hierarchy including the isothermal Euler equations in semilinear form and the stationary Euler equations in purely algebraic form. The focus of the work is on the effect of data uncertainty, discretization, and rounding errors in the numerical simulation of these models and their interaction. Two simple discretization schemes for the semilinear model are compared with respect to their conditioning and temporal stepsizes are determined for which a well-conditioned problem is obtained. The results are based on new componentwise relative condition numbers for the solution of nonlinear systems of equations. More- over, the model error between the semilinear and the algebraic model is computed, the maximum pipeline length is determined for which the algebraic model can be used safely, and a condition is derived for which the isothermal model is adequate.

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12

Shintani, Hisayoshi. "Componentwise error estimates for approximate solutions to systems of equations with the aid of Dahlquist constants." Hiroshima Mathematical Journal 16, no. 3 (1986): 553–71. http://dx.doi.org/10.32917/hmj/1206130308.

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13

Newlands, Nathaniel K., Gabriela Espino-Hernández, and R. Scott Erickson. "Understanding Crop Response to Climate Variability with Complex Agroecosystem Models." International Journal of Ecology 2012 (2012): 1–13. http://dx.doi.org/10.1155/2012/756242.

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Agroecosystem modeling studies often rely on relatively short time-series historical records for training/tuning empirical parameters and to predict long-term variation in crop production associated with trends in climate and hydrological forcing. While ecosystem models may exhibit similar prediction skill in validation studies, their sensitivity to climate variability can differ significantly. Such discrepancy often arises due to the need to tradeoff model complexity with data availability. We examine the sensitivity in predicting spring wheat crop productivity across agricultural sites with differing soil and climate conditions where long-term agronomic and climate records are available. We report significant changes in the model sensitivity accompanying changing climatic regime. If not corrected for, this can lead to substantial predictive error when simulating across time and space. Our findings lend further support for a hierarchical (componentwise) approach for reducing model complexity and improving prediction skill.

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14

Zhmaylov, Vadim V., Andrew Iu Kozhenikov, and Olga A. Korovina. "The application of the nuclear power plant measuring channels complete verification." Izmeritel`naya Tekhnika, no. 5 (2020): 4–10. http://dx.doi.org/10.32446/0368-1025it.2020-5-4-10.

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It’s suggested to develop the additional NPP measuring channels verification regulations in order to reduce verification labour-intensiveness and increase economic NPP operation efficiency. This regulations should afford an opportunity for componentwise verification and for basic and alternative complete verification of the NPP measuring channels depending on the verification reliability requirements. The uniformly precise, cross and combined methods are identified as alternative methods of complete verification. This article proposes the main regulations development problems and presents requirements for the basic regulations provisions. It’s emphasized that the developed regulations of the provisions on the application complete verification of the NPP measuring channels should allow: to control the channel error as a single measuring device without demounting its components; to reduce the verification time allocated during power generating unit hold; to preserve the acceptable level of the measurement channel verification results reliability. An example of the complete verification reliability estimation procedure is given as one of the most important criteria for selecting the verification method.

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15

Rump, Siegfried M. "The Componentwise Structured and Unstructured Backward Errors Can be Arbitrarily Far Apart." SIAM Journal on Matrix Analysis and Applications 36, no. 2 (January 2015): 385–92. http://dx.doi.org/10.1137/140985500.

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16

Heindl, G. "Best possible componentwise parameter inclusions computable from a priori estimates, measurements, and bounds for the measurement errors." Journal of Computational and Applied Mathematics 152, no. 1-2 (March 2003): 175–85. http://dx.doi.org/10.1016/s0377-0427(02)00704-5.

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17

Zhang, Jiacheng, Sayantan Bhattacharya, and Pavlos Vlachos. "Uncertainty of PIV/PTV based pressure, using velocity uncertainty." 14th International Symposium on Particle Image Velocimetry 1, no. 1 (August 1, 2021). http://dx.doi.org/10.18409/ispiv.v1i1.148.

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Pressure reconstruction from velocity measurements using particle image velocimetry (PIV) and particle tracking velocimetry (PTV) has drawn significant attention as it can provide instantaneous pressure fields without altering the flow. Previous studies have found that the accuracy of the calcualted pressure field depends on several factors including the accuarcy of the velocity measurement, the spatiotemporal resolutions, the method for calculating pressure-gradient, the algorithm for pressure-gradient integration, the pressure boundary condition, etc. Therefore, it is critical and challenging to quantify the uncertainty of the reconstructed pressure field. The recent development of the uncertainty quantification algorithms for PIV and PTV allows for the local and instantaneous uncertainty estimation of velocity measurement, which can be used to infer the pressure uncertainty. In this study, we introduce a framework that propagates the standard velocity uncertainty defined as the standard deviation of the velocity error distribution through the pressure reconstruction process to obtain the uncertainty of the pressure field. The uncertainty propagations through the calculation of the pressure-gradient and the pressure-gradient integration were modeled as linear transformations, which can reproduce the effects of the spatiotemporal resolutions, the numerical schemes, the integration algorithms, and the pressure boundary condition on the accuracy of the resulting pressure fields. The proposed uncertainty estimation approach also considers the effect of the spatiotemporal and componentwise correlation of the velocity errors in common PIV/PTV measurements on the pressure uncertainty.

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