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

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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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