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Titlebook: An Introduction to Computational Science; Allen Holder,Joseph Eichholz Textbook 2019 Springer Nature Switzerland AG 2019 Computational Mod

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期刊全稱(chēng)An Introduction to Computational Science
影響因子2023Allen Holder,Joseph Eichholz
視頻videohttp://file.papertrans.cn/156/155187/155187.mp4
發(fā)行地址Completely up-to-date text designed to address the shortfalls of all existing texts available.End-of-chapter problems throughout and online ancillaries available.Authors based the pedagogy on their ow
學(xué)科分類(lèi)International Series in Operations Research & Management Science
圖書(shū)封面Titlebook: An Introduction to Computational Science; Allen Holder,Joseph Eichholz Textbook 2019 Springer Nature Switzerland AG 2019 Computational Mod
影響因子This textbook provides an introduction to the growing interdisciplinary field of computational science. It combines a foundational development of numerical methods with a variety of illustrative applications spread across numerous areas of science and engineering. The intended audience is the undergraduate who has completed introductory coursework in mathematics and computer science. Students gain computational acuity by authoring their own numerical routines and by practicing with numerical methods as they solve computational models. This education encourages students to learn the importance of answering: .How expensive is a calculation, how trustworthy is a calculation,. and .how might we model a problem to apply a desired numerical method?.The text is written in two parts. Part I provides a succinct, one-term inauguration into the primary routines on which a further study of computational science rests. The material is organized so that the transition to computational science from coursework in calculus, differential equations, and linear algebra is natural. Beyond the mathematical and computational content of Part I, students gain proficiency with elemental programming construc
Pindex Textbook 2019
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Stochastic Methods and Simulationhave largely been deterministic, as they have not depended on random elements in their computation—previous exceptions being our studies of linear regression, simulated annealing, and genetic algorithms. These exceptions point to a dichotomy into how randomness leaks itself into the computational ar
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Modeling with Matricesasily slip into the background of computational science. Indeed, most students have likely questioned why they couldn’t simply rely on . as they have studied the numerous ways to solve .?=?. in Chap. .. The answer is, of course, to gain an appreciation of the intrinsic computational difficulty of so
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Modeling with Ordinary Differential Equations They are of such importance that they have spawned much of the mathematics that we know today. Our task here is to model and solve problems to illustrate how computational modeling can aid scientific and engineering pursuits. We consider the three problems of modeling a Couette flow, an insulin bol
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Modeling with Delay Differential Equationsselves to adaptations that more seamlessly capture the entity being modeled. This chapter studies one such adaptation called a delay differential equation (DDE).A DDE is an ordinary differential equation that permits dependencies on historical information, and initial conditions are replaced with le
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