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dc.contributor.authorAmanchi, Srinivas Adithya
dc.description.abstractRecently, in many experimental studies, the statistical analysis of nonparametric comparisons has grown in the area of computational intelligence. The research refers to application of different techniques that are used to show comparison among the algorithms in an experimental study. Pairwise statistical technique perform individual comparison between two algorithms and multiple statistical technique perform comparison between more than two algorithms. Techniques include the Sign test, Wilcoxon signed ranks test, the multiple sign test, the Friedman test, the Friedman aligned ranks test and the Quade test. In this paper, we used these tests to analyze the results obtained in an experimental study comparing well-known algorithms and optimization functions. The analyses showed that the application of statistical tests helps to identify the algorithm that is significantly different than the remaining algorithms in a comparison. Different statistical analyses were conducted on the results of an experimental study obtained with varying dimension size.en_US
dc.publisherNorth Dakota State Universityen_US
dc.rightsNDSU Policy 190.6.2
dc.titleApplied Nonparametric Statistical Tests to Compare Evolutionary and Swarm Intelligence Approachesen_US
dc.typeMaster's paperen_US
dc.date.accessioned2014-04-28T18:43:13Z
dc.date.available2014-04-28T18:43:13Z
dc.date.issued2014
dc.identifier.urihttp://hdl.handle.net/10365/23144
dc.subject.lcshMathematical optimization.en_US
dc.subject.lcshComputational intelligence.en_US
dc.subject.lcshSwarm intelligence.en_US
dc.subject.lcshEvolutionary computation.en_US
dc.subject.lcshNonparametric statistics.en_US
dc.rights.urihttps://www.ndsu.edu/fileadmin/policy/190.pdf
ndsu.degreeMaster of Science (MS)en_US
ndsu.collegeEngineeringen_US
ndsu.departmentComputer Scienceen_US
ndsu.programComputer Scienceen_US
ndsu.advisorLudwig, Simone


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