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Diaz M.H., Cordova F.M., Canete L., Palominos F., Cifuentes F., Sanchez C., Herrera M., Order and Chaos in the Brain: Fractal Time Series Analysis of the EEG Activity during a Cognitive Problem Solving Task, Procedia Computer Science, 55, pp. 1410-1419, (2015)
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Falamarzi A., Moridpour S., Nazem M., Hesami R., Integration of Genetic Algorithm and Support Vector Machine to Predict Rail Track Degradation, MATEC Web of Conferences, 2018 6th International Conference on Traffic and Logistic Engineering (ICTLE 2018), 259, pp. 1-5, (2018)
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Gasmi A., Zouari H., Masse A., Ducrot D., Potential of the Support Vector Machine (Svms) for Clay and Calcium Carbonate Content Classification from Hyperspectral Remote Sensing, International Journal of Innovation and Applied Studies, 13, pp. 497-506, (2015)
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Gonzalez-Serrano F.J., Navia-Vazquez A., Amor-Martin A., Training Support Vector Machines with Privacy-protected Data, Pattern Recognition, 72, pp. 93-107, (2017)
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Holl M., Kiyono K., Kantz H., Theoretical Foundation of Detrending Methods for Fluctuation Analysis Such as Detrended Fluctuation Analysis and Detrending Moving Average, Physical Review E, 99, (2019)
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Likens A.D., Fine J.M., Amazeen E.L., Amazeen P.G., Experimental Control of Scaling Behavior: What Is Not Fractal?, Experimental Brain Research, 233, pp. 2813-2821, (2015)
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Mafarja M.M., Mirjalili S., Whale Optimization Approaches for Wrapper Feature Selection, Applied Soft Computing, 62, pp. 441-453, (2018)
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Moje R.K., Patil C.G., Classification of Satellite Images Based on SVM Classifier Using Genetic Algoritm, International Journal of Innovative Research in Electrical, Electronics, Instrumentation and Control Engineering, 2, pp. 1522-1526, (2014)
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Nazari Z., Kang D., Density Based Support Vector Machines for Classification, International Journal of Advanced Research in Artificial Intelligence, 4, pp. 69-76, (2015)