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APPLICATION OF THE SOFTWARE TOOLS EXPERIMENTAL DESIGN FOR THE GENETIC APPROXIMATION ALGORITHM PARAMETER OPTIMIZATION

Abstract

Experimental optimization of convergence rate of the genetic approximation algorithm accomplished with the application of the specialized scientific design of experiments software tools is described.

About the Author

Vitaly V. VOLKOV
Don State Technical University
Russian Federation


References

1. MATLAB Statistics Toolbox: Product overview page - http://www.mathworks.com/products/statistics, 2010.

2. STATISTICA Data Miner: Overview of software product - http://www.statsoft.com/products/statistica-data-miner, 2010.

3. Stat-Ease: Software overview - http://www.statease.com/software.html, 2010.

4. Volkov V.V. Planirovanie eksperimenta i obrabotka rezul'tatov pri pomoschi programmnogo sredstva EOSupport / V.V. Volkov // Vestn. DGTU. – 2008. – T. 8. – № 2 (37). - in Russian.

5. Scientific Computing Tools For Python: NumPy: - http://numpy.scipy.org, 2009.

6. Performance Python: A comparison of weave with NumPy, Pyrex, Psyco, Fortran (77 and 90) and C++ for solving Laplace's equation - http://www.scipy.org/PerformancePython, 2009, нояб.

7. Matplotlib: Python plotting: - http://matplotlib.sourceforge.net, 2008.


Review

For citations:


VOLKOV V. APPLICATION OF THE SOFTWARE TOOLS EXPERIMENTAL DESIGN FOR THE GENETIC APPROXIMATION ALGORITHM PARAMETER OPTIMIZATION. Vestnik of Don State Technical University. 2010;10(4):487-491. (In Russ.)

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ISSN 2687-1653 (Online)