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  2. Subset sum problem - Wikipedia

    en.wikipedia.org/wiki/Subset_sum_problem

    SSP can also be regarded as an optimization problem: find a subset whose sum is at most T, and subject to that, as close as possible to T. It is NP-hard, but there are several algorithms that can solve it reasonably quickly in practice. SSP is a special case of the knapsack problem and of the multiple subset sum problem.

  3. Structural synthesis of programs - Wikipedia

    en.wikipedia.org/wiki/Structural_synthesis_of...

    Structural synthesis of programs (SSP) is a special form of (automatic) program synthesis that is based on propositional calculus.More precisely, it uses intuitionistic logic for describing the structure of a program in such a detail that the program can be automatically composed from pieces like subroutines or even computer commands.

  4. Simplified perturbations models - Wikipedia

    en.wikipedia.org/wiki/Simplified_perturbations...

    Simplified perturbations models are a set of five mathematical models (SGP, SGP4, SDP4, SGP8 and SDP8) used to calculate orbital state vectors of satellites and space debris relative to the Earth-centered inertial coordinate system.

  5. Maximum subarray problem - Wikipedia

    en.wikipedia.org/wiki/Maximum_subarray_problem

    Each possible contiguous sub-array is represented by a point on a colored line. That point's y-coordinate represents the sum of the sample. Its x-coordinate represents the end of the sample, and the leftmost point on that colored line represents the start of the sample. In this case, the array from which samples are taken is [2, 3, -1, -20, 5, 10].

  6. SPSS Modeler - Wikipedia

    en.wikipedia.org/wiki/SPSS_Modeler

    IBM SPSS Modeler is a data mining and text analytics software application from IBM.It is used to build predictive models and conduct other analytic tasks. It has a visual interface which allows users to leverage statistical and data mining algorithms without programming.

  7. Nonlinear conjugate gradient method - Wikipedia

    en.wikipedia.org/wiki/Nonlinear_conjugate...

    These formulas are equivalent for a quadratic function, but for nonlinear optimization the preferred formula is a matter of heuristics or taste. A popular choice is β = max { 0 , β P R } {\displaystyle \displaystyle \beta =\max\{0,\beta ^{PR}\}} , which provides a direction reset automatically.

  8. Algorithms for calculating variance - Wikipedia

    en.wikipedia.org/wiki/Algorithms_for_calculating...

    Algorithms for calculating variance play a major role in computational statistics.A key difficulty in the design of good algorithms for this problem is that formulas for the variance may involve sums of squares, which can lead to numerical instability as well as to arithmetic overflow when dealing with large values.

  9. Plotting algorithms for the Mandelbrot set - Wikipedia

    en.wikipedia.org/wiki/Plotting_algorithms_for...

    The simplest algorithm for generating a representation of the Mandelbrot set is known as the "escape time" algorithm. A repeating calculation is performed for each x, y point in the plot area and based on the behavior of that calculation, a color is chosen for that pixel.