Stack Overflow
Stack Overflow

Questions tagged [approximation]

Approximation algorithms are algorithms used to find approximate solutions to optimization problems.

Approximation algorithms are algorithms which generate feasible solutions to optimizazion algorithms. Although permitted to generate solution which are not optimal, there is an algorithm-dependent bound for the ratio of the objective of an optimum and the objective of the generated solution; this ratio is termed the approximation ratio.

Useful links

Related tags

523 questions
0
votes
1 answer

GIS: Tunnel to geographical distance approximation

This question is more about math than programming. I am programming a function which takes a square of geographical distance between 2 points with known latitude and longitude as an argument. There's a straightforward way to compute it: calculate…
antonio
  • 375
  • 4
  • 13
0
votes
0 answers

Image resizing using approximation

I've been given a task to make image resizing using approximation. The problem is that i have no idea how may it works. The previous task was to do this using interpolation, and everything was clear about that. Now i need to use approximation. So…
user3742345
  • 13
  • 3
0
votes
1 answer

singular value decomposition and low rank tensorial approximation

according this article http://www.wseas.us/e-library/conferences/2012/Vouliagmeni/MMAS/MMAS-07.pdf matrix can be approximated by one rank matrices using tensorial approximation,i know that in matlab kronecker product plays same role as …
user466534
0
votes
1 answer

Find parabola by set of points in python

I have a set of points like X = [1, 2, 3, 4, 5, ..] Y = [9, 7, 5, 3, 5, ..] I need to find interpolation parabola for Y like it's done my MNK method for lines. Is there any functions in NumPy maybe? Im not really good at therms of quadratic…
aromatvanili
  • 175
  • 4
  • 12
0
votes
1 answer

How to implement the adaptive heun's method in python?

I'm trying to implement code for Heun's method function. But I'm also doing it in the adaptive style. Regularly for say rectangle method, if you do adaptive style, you compare the area from a to b, with the sum of a to the center of a and b and then…
omega
  • 40,311
  • 81
  • 251
  • 474
0
votes
2 answers

Euler's Method In Matlab

I am working on a problem involves my using the Euler Method to approximate the differential equation df/dt= af(t)−b[f(t)]^2, both when b=0 and when b is not zero; and I am to compare the analytic solution to the approximate solution when b=0. f(1)…
Mack
  • 665
  • 2
  • 11
  • 20
0
votes
1 answer

Euler's programming function : differential equation as a parameter

I have a programming function written for Eurler's approximations. Currently the function only takes 3 parameters. step size starting f(x) endting f(x) which is what we are approximating Each time I have to use Euler, I have to keep on changing my…
aspiring
  • 1,557
  • 2
  • 20
  • 43
0
votes
1 answer

Bound Principle for Integer Linear Programming and Linear Programming

Currently, I am learning approximation algorithms. When I learned Vertex Cover via LP, I encountered a principle called Bounding Principles. It like this: (1) The maximum value for an ILP problem is always less than or equal to the maximum value…
CSnerd
  • 2,129
  • 8
  • 22
  • 45
0
votes
2 answers

travelling sales man for an incomplete graph

i have a large weighted graph.i want to compute an approximate shortest hamiltonian path which goes through all nodes with the lowest cost. my graph is really big that it doesn't fit in my memory. so i decided to randomly ignore some edges and load…
Soheila DehghanZadeh
  • 379
  • 2
  • 4
  • 14
0
votes
3 answers

Good way to approximate a floating point number

I have a program that solves equations and sometimes the solutions x1 and x2 are numbers with a lot of decimal numbers. For example when Δ = 201 (Δ = discriminant) the square root gives me a floating point number. I need a good approximation of that…
Alberto Rossi
  • 1,800
  • 4
  • 36
  • 58
0
votes
1 answer

Finding approximation function which depend on 8-parameters

I have a lot entries of data, each entry consists of 8 (eight) numbers. For each entry I know "fitness score" (i.e. how "good" this entry). And, I want to build/find approximation function ("fitness score" dependent on those 8 parameters). Not only…
Arsen
  • 153
  • 1
  • 12
0
votes
2 answers

will this sinus approximation be faster than a shader CG sinus function?

I have some functions that are not really sines but they are a lot quicker than conventional processing, they are simple parabole functions. Will this be faster on a graphics processor than the built-in graphics sinus function: float par (float…
bandybabboon
  • 2,210
  • 1
  • 23
  • 33
0
votes
1 answer

IEEE floating points implementation, precision and accumulation of approximations

If I understand IEEE floating points correctly, they are unable to accurately represent some values. They are accurate in very limited cases and pretty much every floating point operation increases the accumulated approximations. Also, another…
user2341104
0
votes
1 answer

Optimization block in python (scipy) - a histogram with a histogram

I need to fit an experimental histogram by a simulated one (to determine several parameters of the simulated one with which it fits best). I've tried curve_fit from scipy.optimize, but it does not work in this case: an error "... is not a python…
Alexandra Shchukina
  • 547
  • 1
  • 4
  • 6
0
votes
5 answers

fast small angle sinus/cosinus approximation

I'm doing some rigid-body rotation dynamics simulation, which means I have to compute many rotations by small angle, which has performance bottleneck in evaluation of trigonometric function. Now I do it by Taylor(McLaurin) series: class double2{ …
Prokop Hapala
  • 2,424
  • 2
  • 30
  • 59
1 2 3
…
34 35