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Titlebook: Error Control and Adaptivity in Scientific Computing; Haydar Bulgak,Christoph Zenger Book 1999 Springer Science+Business Media Dordrecht 1

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書目名稱Error Control and Adaptivity in Scientific Computing
編輯Haydar Bulgak,Christoph Zenger
視頻videohttp://file.papertrans.cn/315/314915/314915.mp4
叢書名稱Nato Science Series C:
圖書封面Titlebook: Error Control and Adaptivity in Scientific Computing;  Haydar Bulgak,Christoph Zenger Book 1999 Springer Science+Business Media Dordrecht 1
描述One of the main ways by which we can understand complexprocesses is to create computerised numerical simulation models ofthem. Modern simulation tools are not used only by experts, however,and reliability has therefore become an important issue, meaning thatit is not sufficient for a simulation package merely to print out somenumbers, claiming them to be the desired results. An estimate of theassociated error is also needed. The errors may derive from manysources: errors in the model, errors in discretization, roundingerrors, etc. .Unfortunately, this situation does not obtain for current packages andthere is a great deal of room for improvement. Only if the error canbe estimated is it possible to do something to reduce it. Thecontributions in this book cover many aspects of the subject, the maintopics being error estimates and error control in numerical linearalgebra algorithms (closely related to the concept of conditionnumbers), interval arithmetic and adaptivity for continuous models.
出版日期Book 1999
關(guān)鍵詞algorithm; algorithms; computer; construction; linear algebra; model; scientific computing; simulation; stab
版次1
doihttps://doi.org/10.1007/978-94-011-4647-0
isbn_softcover978-0-7923-5809-1
isbn_ebook978-94-011-4647-0Series ISSN 1389-2185
issn_series 1389-2185
copyrightSpringer Science+Business Media Dordrecht 1999
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Error Estimates in Linear Systems,, when solving it by an iterative procedure, a sequence of approximate solutions is constructed. We will denote by .* an approximation of . = .... Usually the quality of the approximate solution is judged by the norm of the residual vector . = . — .*.
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Error Control for Adaptive Sparse Grids,vantageous for a wide spectrum of numerical topics, especially in situations where adaptively refined grids have to be taken into account. Starting from a really classic example, Archimedes’ solution to the problem of integrating a parabola segment, we discuss the impact of such design patterns on n
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Adaptive Symplectic and Reversible Integrators,rvation of the original model of the underlying physical problem became very important in recent years. It has been shown theoretically and experimentally, that these methods are superior to the standard integrators, especially in long term computation. In the paper the adaptivity issues are discuss
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The Accuracy of Numerical Models for Continuum Problems, to some extent, electromagnetics. I focus lots of attention on geometry and grids as constructing this part of the model easily consumes much of the modeling effort. I also place a strong emphasis on understanding the conservation and material laws that underly the modeling, and because these laws
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