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A point on a graph, when all nearby points have a smaller value, is called a maximum.
An argmax is a mathematical term for the argument of the maximum - the set of points of a given argument for which a given function attains its maximum value.
To determine the maximum displacement, you need to calculate the peak value of the displacement function. This is done by finding the extreme values (maximum or minimum) of the function, typically by taking the derivative and setting it to zero to find critical points. Once you have these critical points, evaluate the function at those points to find the maximum displacement.
The maximum value of a feasible region, typically in the context of linear programming, occurs at one of the vertices or corner points of the region. This is due to the properties of linear functions, which achieve their extrema at these points rather than within the interior of the feasible region. To find the maximum value, you evaluate the objective function at each vertex and select the highest result.
In Calculus, to find the maximum and minimum value, you first take the derivative of the function then find the zeroes or the roots of it. Once you have the roots, you can just simply plug in the x value to the original function where y is the maximum or minimum value. To know if its a maximum or minimum value, simply do your number line to check. the x and y are now your max/min points/ coordinates.
What is maximum value
To find the maximum value of (2x + 2y) in the feasible region, you typically need to identify the constraints that define this region, often in the form of inequalities. Then, you would evaluate the objective function at the vertices of the feasible region, which are the points of intersection of the constraints. The maximum value will be found at one of these vertices. If you provide the specific constraints, I can help you calculate the maximum value.
An absolute maximum refers to the highest value of a function over its entire domain. It occurs at a specific point where the function reaches its greatest output compared to all other points in that domain. This value is distinct from relative maxima, which are the highest points in a localized area but not necessarily the highest overall. Identifying the absolute maximum is important in optimization problems and calculus.
Having a minimum and maximum on a graph refers to the lowest and highest points of a function within a given interval. The minimum represents the lowest value that the function reaches, while the maximum indicates the highest value. These points are crucial in understanding the overall behavior of the function, as they can signify where the function changes direction or reaches its extremities. Identifying these points helps in analyzing trends, optimizing values, and solving real-world problems.
An "extreme value" is either a local maximum, or a local minimum - i.e., a point which is greater than all the points in a certain neighborhood, or less than all points in a certain neighborhood.
A local maximum in a table refers to a value that is greater than its immediate neighbors in the dataset. In a two-dimensional table, this means a value is a local maximum if it is greater than the values directly adjacent to it—vertically and horizontally. Local maxima can indicate points of interest or peaks in the data, but they do not necessarily represent the highest value in the entire dataset.
A minimum of a function is the lowest value that the function can attain within a given domain, while a maximum is the highest value it can reach. These points can occur at specific input values (local minima or maxima) or over the entire domain (global minima or maxima). Identifying these points is crucial in optimization problems and helps in understanding the behavior of the function.