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Ontologies to Lead Knowledge Intensive Evolutionary Algorithms: Principles and Case Study.

, , , and . IJKSS, 7 (1): 78-100 (2016)

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Ontologies to Lead Knowledge Intensive Evolutionary Algorithms: Principles and Case Study., , , and . IJKSS, 7 (1): 78-100 (2016)A Multi Objective Evolutionary Algorithm for Solving a Real Health Care Fleet Optimization Problem., , , and . KES, volume 60 of Procedia Computer Science, page 256-265. Elsevier, (2015)Datasets are not enough: Challenges in labeling network traffic., , and . Comput. Secur., (2022)An autonomous labeling approach to support vector machines algorithms for network traffic anomaly detection., , and . Expert Syst. Appl., 39 (2): 1822-1829 (2012)DNS Tunneling: A Deep Learning based Lexicographical Detection Approach., , , , and . CoRR, (2020)Deep Convolutional Neural Networks for DGA Detection., , and . CACIC, volume 995 of Communications in Computer and Information Science, page 327-340. Springer, (2018)Network traffic pattern recognition based on genetic algorithms., and . Inteligencia Artif., 12 (37): 65-75 (2008)LLM in the Shell: Generative Honeypots., , , and . CoRR, (2023)Beyond Random Split for Assessing Statistical Model Performance., , , , and . CoRR, (2022)A statistical approach for optimal order adjustment of a moving average filter., and . PLANS, page 1542-1546. IEEE, (2018)