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  2. Isocline - Wikipedia

    en.wikipedia.org/wiki/Isocline

    Isoclines are often used as a graphical method of solving ordinary differential equations. In an equation of the form y' = f(x, y), the isoclines are lines in the (x, y) plane obtained by setting f(x, y) equal to a constant. This gives a series of lines (for different constants) along which the solution curves have the same gradient.

  3. Slope - Wikipedia

    en.wikipedia.org/wiki/Slope

    Slope illustrated for y = (3/2)x − 1.Click on to enlarge Slope of a line in coordinates system, from f(x) = −12x + 2 to f(x) = 12x + 2. The slope of a line in the plane containing the x and y axes is generally represented by the letter m, [5] and is defined as the change in the y coordinate divided by the corresponding change in the x coordinate, between two distinct points on the line.

  4. Grade (slope) - Wikipedia

    en.wikipedia.org/wiki/Grade_(slope)

    l = slope length α = angle of inclination. The grade (US) or gradient (UK) (also called stepth, slope, incline, mainfall, pitch or rise) of a physical feature, landform or constructed line is either the elevation angle of that surface to the horizontal or its tangent. It is a special case of the slope, where zero indicates horizontality. A ...

  5. Conjugate residual method - Wikipedia

    en.wikipedia.org/wiki/Conjugate_residual_method

    The conjugate residual method is an iterative numeric method used for solving systems of linear equations. It's a Krylov subspace method very similar to the much more popular conjugate gradient method, with similar construction and convergence properties. This method is used to solve linear equations of the form

  6. Gekko (optimization software) - Wikipedia

    en.wikipedia.org/wiki/Gekko_(optimization_software)

    Optimal control is the use of mathematical optimization to obtain a policy that is constrained by differential (=), equality (() =), or inequality (()) equations and minimizes an objective/reward function (()). The basic optimal control is solved with GEKKO by integrating the objective and transcribing the differential equation into algebraic ...

  7. Finite difference method - Wikipedia

    en.wikipedia.org/wiki/Finite_difference_method

    For example, consider the ordinary differential equation ′ = + The Euler method for solving this equation uses the finite difference quotient (+) ′ to approximate the differential equation by first substituting it for u'(x) then applying a little algebra (multiplying both sides by h, and then adding u(x) to both sides) to get (+) + (() +).

  8. Matrix-free methods - Wikipedia

    en.wikipedia.org/wiki/Matrix-free_methods

    It is generally used in solving non-linear equations like Euler's equations in computational fluid dynamics. Matrix-free conjugate gradient method has been applied in the non-linear elasto-plastic finite element solver. [7] Solving these equations requires the calculation of the Jacobian which is costly in terms of CPU time and storage. To ...

  9. Xcas - Wikipedia

    en.wikipedia.org/wiki/Xcas

    Figure 2. Xcas can solve equations, calculate derivatives, antiderivatives and more. Figure 3. Xcas can solve differential equations. Xcas is a user interface to Giac, which is an open source [2] computer algebra system (CAS) for Windows, macOS and Linux among many other platforms. Xcas is written in C++. [3]