Longstaff: "Genetic algorithm optimization of adaptive multi-scale GLCM features", International Journal of Pattern Recognition and Artificial Intelligence, vol. 17, no. 1, pp. 17-39, 2003.R.F. Walker, P.T. Jack
Applying the genetic algorithm: In the first step of the proposed method, a version of GA is used for the FS56. In different FS studies, CSs are binary, while their length is constant and equal to the total number of features. In this study, for both GA and WCC algorithms, CSs have ...
Secondly, these feature vectors as the input of BP neural network are trained and modeled and then the Genetic Algorithm is used to optimize the BP Neural Network. Finally, the signal's type is determined according to the output of Neural Network. The experiments show that the correct rate ...
Nuffield Department of Medicine, The Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK Markus Ralser Max Planck Institute for Molecular Genetics, Berlin, Germany Markus Ralser Contributions K.L.Y. developed the algorithm, wrote the software, and analyzed the results. F.Y. assist...
Two different types of feature selection algorithms, a simple Genetic Algorithm (GA) and the Relief algo- rithm are applied to select the moment features that better discriminate human faces and facial expressions, under several pose and illumination conditions. Appropriate experiments using four bench...
Perez. Selection of relevant features in a fuzzy genetic learning algorithm. IEEE Trans. on Systems, Man, and Cybernetics - Part B: Cybernetics 31:3 (2001) 417-425.A. González and R. Perez, "Selection of relevant features in a fuzzy genetic learning algorithm", IEEE Trans. Syst., Man ...
Optimization of an aluminum alloy anti-collision side beam hot stamping process using a multi-objective genetic algorithm Arch. Civ. Mech. Eng., 13 (2013), pp. 401-411, 10.1016/j.acme.2013.01.008 View PDFView articleView in ScopusGoogle Scholar Zhou et al., 2014 Zhou J., Wang B.Y.,...
We note that the absence of our proposed genetic biomarkers does not rule out HBCs because of the limitations of our study, which may have not detected the entire spectrum of genetic and epigenetic abnormalities. Interestingly, our study suggested a broad age range for patients with HBCs, as ...
It requires two user-defined parameters: the number of Gaussian components (k) and the number of individuals for the initial population in the genetic algorithm (N). The first was kept six as in [18], and N was set to 100k, instead of 10k. High values of N implicate in more running...
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