By Abhaya Chandra Kammara, Andreas König (auth.), Václav Snášel, Pavel Krömer, Mario Köppen, Gerald Schaefer (eds.)
This quantity of Advances in clever platforms and Computing comprises authorized papers offered at WSC17, the seventeenth on-line global convention on delicate Computing in business functions, held from December 2012 to January 2013 on the net. WSC17 maintains a profitable sequence of medical occasions begun over a decade in the past by way of the area Federation of soppy Computing. It introduced jointly researchers from over the realm attracted to the ever advancing state-of-the-art within the box. non-stop technological advancements make this on-line discussion board a plausible amassing layout for a global classification convention. the purpose of WSC17 was once to disseminate very good examine effects and give a contribution to development an international community of scientists drawn to either theoretical foundations and sensible purposes of sentimental computing.
The 2012 variation of the net global convention on delicate Computing in commercial functions consisted of normal song and certain consultation on non-stop positive aspects Discretization for Anomaly Intrusion Detectors iteration and precise consultation on rising Theories and purposes in Transportation technology. a complete of 33 top of the range learn papers have been accredited after a rigorous assessment strategy and are supplied during this book.
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Additional info for Soft Computing in Industrial Applications: Proceedings of the 17th Online World Conference on Soft Computing in Industrial Applications
Optimiz. Theory App. 8(3), 161–168 (1971) 7. : Traffic assignment modelling. , Nijkamp, P. ) A Dictionary of Transport Analysis, PP. 418–420. Edward Elgar, Cheltenham (2010) 8. : Solving transportation bi-level programs with differential evolution. Proceedings of the IEEE Congress on Evolutionary Computation, pp. 2243–2250. IEEE Press, Piscataway, New Jersey (2007) 9. : An evolutionary algorithm based on Nash dominance for equilibrium problems with equilibrium constraints. Appl. Soft Comput. 12(1), 161–173 (2012) 10.
Therefore, as can be seen in Fig. 3b, in SGP the genotypic diversity is higher than in GP. A second set of experiments aims to answer to the hard question whether populations with higher phenotypic or genotypic diversity can obtain a better solution. In practice, we want to investigate the correlation between the fitness and these measures of diversity. Similar to , Spearman correlation is adopted in order to determinate if a relation between fitness and diversity exists. The Spearman correlation can be N P 2 6 di defined as 1 À Ni¼1 3 ÀN , where di is the difference between the rank of the best fitness and the rank of the diversity of population i.
Therefore the pool consisted of eight different neural networks. Neural network architecture was as follows: the number of neurons in the input layer was equal to the number of selected features, the number of output neurons was equal to the number of classes and the number of hidden neurons was equal to the half of the sum of number of neurons from the former layers, as suggested in. Quickprop algorithm was used as a training procedure. 3. As reference methods we have selected most popular ensembles—Bagging, Boosting, Random Forest and Random Subspace—as they were used in our previous work —in there one may also find the details of used parameters for these ensemble classifiers.
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