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This paper describes a novel virtual population based truncation selection operator that extends our previously proposed virtual population based tournament selection operator. Moreover, two extensions of compact genetic algorithm (CGA) that make use of virtual population based selection operators are presented in this paper: one is the tournament selection on virtual population based compact genetic...
Clustering is traditionally viewed as an unsupervised method for data analysis. However, several recent studies have shown that some limited prior instance-level knowledge can significantly improve the performance of clustering algorithm. This paper proposes a semi-supervised clustering algorithm termed as the probabilistic and graphical model based genetic algorithm driven clustering with instance-level...
Classification of intrusion attacks and normal network traffic is a challenging and critical problem in pattern recognition and network security. In this paper, we present a novel intrusion detection approach to extract both accurate and interpretable fuzzy IF–THEN rules from network traffic data for classification. The proposed fuzzy rule-based system is evolved from an agent-based evolutionary framework...
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