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  2. Universal parabolic constant - Wikipedia

    en.wikipedia.org/wiki/Universal_parabolic_constant

    The universal parabolic constant is the red length divided by the green length. The universal parabolic constant is a mathematical constant.. It is defined as the ratio, for any parabola, of the arc length of the parabolic segment formed by the latus rectum to the focal parameter.

  3. Parabola - Wikipedia

    en.wikipedia.org/wiki/Parabola

    In the theory of quadratic forms, the parabola is the graph of the quadratic form x 2 (or other scalings), while the elliptic paraboloid is the graph of the positive-definite quadratic form x 2 + y 2 (or scalings), and the hyperbolic paraboloid is the graph of the indefinite quadratic form x 2 − y 2. Generalizations to more variables yield ...

  4. Newton's method in optimization - Wikipedia

    en.wikipedia.org/wiki/Newton's_method_in...

    The geometric interpretation of Newton's method is that at each iteration, it amounts to the fitting of a parabola to the graph of () at the trial value , having the same slope and curvature as the graph at that point, and then proceeding to the maximum or minimum of that parabola (in higher dimensions, this may also be a saddle point), see below.

  5. Parabola of safety - Wikipedia

    en.wikipedia.org/wiki/Parabola_of_safety

    In 2D and shooting on a horizontal plane, parabola of safety can be represented by the equation y = u 2 2 g − g x 2 2 u 2 {\displaystyle y={\frac {u^{2}}{2g}}-{\frac {gx^{2}}{2u^{2}}}} where u {\displaystyle u} is the initial speed of projectile and g {\displaystyle g} is the gravitational field.

  6. Rosenbrock function - Wikipedia

    en.wikipedia.org/wiki/Rosenbrock_function

    Plot of the Rosenbrock function of two variables. Here =, =, and the minimum value of zero is at (,).. In mathematical optimization, the Rosenbrock function is a non-convex function, introduced by Howard H. Rosenbrock in 1960, which is used as a performance test problem for optimization algorithms. [1]

  7. Proofs involving ordinary least squares - Wikipedia

    en.wikipedia.org/wiki/Proofs_involving_ordinary...

    The normal equations can be derived directly from a matrix representation of the problem as follows. The objective is to minimize = ‖ ‖ = () = +.Here () = has the dimension 1x1 (the number of columns of ), so it is a scalar and equal to its own transpose, hence = and the quantity to minimize becomes

  8. Johnson's parabolic formula - Wikipedia

    en.wikipedia.org/wiki/Johnson's_parabolic_formula

    Graph of Johnson's parabola (plotted in red) against Euler's formula, with the transition point indicated. The area above the curve indicates failure. The Johnson parabola creates a new region of failure. In structural engineering, Johnson's parabolic formula is an empirically based equation for calculating the critical buckling stress of a column.

  9. Calculus of variations - Wikipedia

    en.wikipedia.org/wiki/Calculus_of_Variations

    These equations for solution of a first-order partial differential equation are identical to the Euler–Lagrange equations if we make the identification = ˙ ˙. We conclude that the function ψ {\displaystyle \psi } is the value of the minimizing integral A {\displaystyle A} as a function of the upper end point.