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We refer to second-order cone programs as deterministic second-order cone programs since data defining them are deterministic. Stochastic second-order cone programs are a class of optimization problems that are defined to handle uncertainty in data defining deterministic second-order cone programs. [10]
In project management, the cone of uncertainty describes the evolution of the amount of best case uncertainty during a project. [1] At the beginning of a project, comparatively little is known about the product or work results, and so estimates are subject to large uncertainty.
The project management triangle. The project management triangle (called also the triple constraint, iron triangle and project triangle) is a model of the constraints of project management. While its origins are unclear, it has been used since at least the 1950s. [1] It contends that:
In mathematical logic, monadic second-order logic (MSO) is the fragment of second-order logic where the second-order quantification is limited to quantification over sets. [1] It is particularly important in the logic of graphs , because of Courcelle's theorem , which provides algorithms for evaluating monadic second-order formulas over graphs ...
A (existential second-order) formula is one additionally having some existential quantifiers over second order variables, i.e. …, where is a first-order formula. The fragment of second-order logic consisting only of existential second-order formulas is called existential second-order logic and abbreviated as ESO, as , or even as ∃SO.
Second-order approximation is the term scientists use for a decent-quality answer. Few simplifying assumptions are made, and when a number is needed, an answer with two or more significant figures ("the town has 3.9 × 10 3, or thirty-nine hundred, residents") is generally given. As in the examples above, the term "2nd order" refers to the ...
If all second-order partial derivatives of exist, then the Hessian matrix of is a square matrix, usually defined and arranged as = []. That is, the entry of the i th row and the j th column is ( H f ) i , j = ∂ 2 f ∂ x i ∂ x j . {\displaystyle (\mathbf {H} _{f})_{i,j}={\frac {\partial ^{2}f}{\partial x_{i}\,\partial x_{j}}}.}
First-order means that only the first derivative of y appears in the equation, and higher derivatives are absent. Without loss of generality to higher-order systems, we restrict ourselves to first-order differential equations, because a higher-order ODE can be converted into a larger system of first-order equations by introducing extra variables.