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  2. Haversine formula - Wikipedia

    en.wikipedia.org/wiki/Haversine_formula

    The haversine formula determines the great-circle distance between two points on a sphere given their longitudes and latitudes.Important in navigation, it is a special case of a more general formula in spherical trigonometry, the law of haversines, that relates the sides and angles of spherical triangles.

  3. Geographical distance - Wikipedia

    en.wikipedia.org/wiki/Geographical_distance

    Geographical distance or geodetic distance is the distance measured along the surface of the Earth, or the shortest arch length. The formulae in this article calculate distances between points which are defined by geographical coordinates in terms of latitude and longitude. This distance is an element in solving the second (inverse) geodetic ...

  4. Minkowski distance - Wikipedia

    en.wikipedia.org/wiki/Minkowski_distance

    The Minkowski distance can also be viewed as a multiple of the power mean of the component-wise differences between and . The following figure shows unit circles (the level set of the distance function where all points are at the unit distance from the center) with various values of :

  5. Great-circle distance - Wikipedia

    en.wikipedia.org/wiki/Great-circle_distance

    A diagram illustrating great-circle distance (drawn in red) between two points on a sphere, P and Q. Two antipodal points, u and v are also shown. The great-circle distance, orthodromic distance, or spherical distance is the distance between two points on a sphere, measured along the great-circle arc between them. This arc is the shortest path ...

  6. Chebyshev distance - Wikipedia

    en.wikipedia.org/wiki/Chebyshev_distance

    In mathematics, Chebyshev distance (or Tchebychev distance), maximum metric, or L ∞ metric [1] is a metric defined on a real coordinate space where the distance between two points is the greatest of their differences along any coordinate dimension. [2] It is named after Pafnuty Chebyshev.

  7. Similarity measure - Wikipedia

    en.wikipedia.org/wiki/Similarity_measure

    The Euclidean distance is a measure of the straight-line distance between two points in a high-dimensional space. It is calculated as the square root of the sum of the squared differences between the corresponding coordinates of the two points.