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Visualizing a genetic algorithm. GA) are one of the standard optimization methods. They work by evolving a population of trial solutions towards better solutions using biological inspired genetic operators. The trial solutions are also called individuums. The above graphics shows the evolution of a particular genetic algorithm – genetic programming. 8211; solving a problem of symbolic regression. The full visualization with additional explanation can be found here. This entry was posted in Uncategorized.

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Visualizing a genetic algorithm. GA) are one of the standard optimization methods. They work by evolving a population of trial solutions towards better solutions using biological inspired genetic operators. The trial solutions are also called individuums. The above graphics shows the evolution of a particular genetic algorithm – genetic programming. 8211; solving a problem of symbolic regression. The full visualization with additional explanation can be found here. This entry was posted in Uncategorized.

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Karsten Ahnert | karstenahnert.com Reviews

https://karstenahnert.com

Visualizing a genetic algorithm. GA) are one of the standard optimization methods. They work by evolving a population of trial solutions towards better solutions using biological inspired genetic operators. The trial solutions are also called individuums. The above graphics shows the evolution of a particular genetic algorithm – genetic programming. 8211; solving a problem of symbolic regression. The full visualization with additional explanation can be found here. This entry was posted in Uncategorized.

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karstenahnert.com

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odeint speaks OpenCL | Karsten Ahnert

http://www.karstenahnert.com/odeint-speaks-opencl

In the previous post I wrote some words about VexCL, a library for OpenCL. This library can easily be used within odeint. I only needed to create an adapter for the odeint resizing mechanism and then it was done. VexCL supports expression template and therefore, it can be used with odeints vector space algebra and default operations. Here is an example of a parameter study of the Lorenz system:. Include boost/numeric/odeint/external/vexcl/vexcl resize.hpp. Vector type ;. State type ;. Sys func {.

2

Software | Karsten Ahnert

http://www.karstenahnert.com/software

Odeint is a C library for solving ordinary differential equations. It provides explicit methods like Euler, various Runge-Kutta solvers, as well as adaptive step-size integration and the Burlisch-Stoer algorithm. Furthermore, solvers for Hamiltonian systems are implemented. Further development will go in the direction of implicit solvers, stiff problems and CUDA support. Proudly powered by WordPress.

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sfinae | Karsten Ahnert

http://www.karstenahnert.com/tag/sfinae

Some days ago a had a little Aha effect about Sfinae (Substitution failure is not an error). I know about Sfinae for a while and I know about the enable if library. In the current standard and in the boost libraries, but I was not aware of all its usefulness. Continue reading →. This entry was posted in Coding. July 29, 2012. Proudly powered by WordPress.

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karsten | Karsten Ahnert

http://www.karstenahnert.com/author/karsten

I do physics, programming, consulting and many more. Visualizing a genetic algorithm. GA) are one of the standard optimization methods. They work by evolving a population of trial solutions towards better solutions using biological inspired genetic operators. The trial solutions are also called individuums. The above graphics shows the evolution of a particular genetic algorithm – genetic programming. 8211; solving a problem of symbolic regression. This entry was posted in Uncategorized. May 13, 2015.

5

cuda | Karsten Ahnert

http://www.karstenahnert.com/tag/cuda

In the previous post I wrote some words about VexCL, a library for OpenCL. This library can easily be used within odeint. I only needed to create an adapter for the odeint resizing mechanism and then it was done. VexCL supports expression template and therefore, it can be used with odeints vector space algebra and default operations. Continue reading →. This entry was posted in Coding. June 25, 2012. Proudly powered by WordPress.

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Karsten Ahnert

Visualizing a genetic algorithm. GA) are one of the standard optimization methods. They work by evolving a population of trial solutions towards better solutions using biological inspired genetic operators. The trial solutions are also called individuums. The above graphics shows the evolution of a particular genetic algorithm – genetic programming. 8211; solving a problem of symbolic regression. The full visualization with additional explanation can be found here. This entry was posted in Uncategorized.

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