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Optimization Algorithms Testing and Convergence by Using a Stacked HistogramZAPLATILEK, K. , TALPA, M. , LEUCHTER, J.
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MATLAB, convergence, optimization, stacked histogram, stochastic system
zaplatilek(4), optimization(4), group(4), delay(4), algorithm(4)
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About this article
Date of Publication: 2011-02-27
Volume 11, Issue 1, Year 2011, On page(s): 11 - 16
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2011.01002
Web of Science Accession Number: 000288761800002
SCOPUS ID: 79955947165
The article describes an original method of optimization algorithms testing and convergence. The method is based on so-called stacked histogram. Stacked histogram is a histogram with its features marked by a chosen colour scheme. Thus, the histogram maintains the information on the input digital sequence. This approach enables an easy identification of the hidden defects in the random process statistical distribution. The stacked histogram is used for the testing of the convergent quality of various optimization techniques. Its width, position and colour scheme provides enough information on the chosen algorithm optimization trajectory. Both the classic iteration techniques and the stochastic optimization algorithm with the adaptation were used as examples.
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 System Optimization Using a Parallel Stochastic Approach, ZAPLATILEK, K., LEUCHTER, J., Advances in Electrical and Computer Engineering, ISSN 1582-7445, Issue 2, Volume 13, 2013.
Digital Object Identifier: 10.4316/AECE.2013.02012 [CrossRef] [Full text]
 Comparing the Robustness of Evolutionary Algorithms on the Basis of Benchmark Functions, DENIZ ULKER, E., HAYDAR, A., Advances in Electrical and Computer Engineering, ISSN 1582-7445, Issue 2, Volume 13, 2013.
Digital Object Identifier: 10.4316/AECE.2013.02010 [CrossRef] [Full text]
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Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania
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