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This paper describes the clustering problem first, and then utilizes the genetic algorithm to implement the optimization of clustering methods. Based on the optimized clustering on the sample data, we get various categories of the relation between traffics and attack amounts, and then builds up several prediction sub-models about DoS attack. Furthermore, according to the Bayesian method, we deduce...
Recent advances in high throughput microarray data have enabled the learning of the structure and operation of gene regulatory networks. This paper proposes a novel approach for reconstruction of gene regulatory networks based on the posterior probabilities of gene regulations. Built within the framework of Bayesian statistics and exploiting efficient computational Monte Carlo techniques, the proposed...
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