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Bin Hu
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Analysis of Brownian Particles for finding the shortest path in networks Bin Hu; jia li xu; huan yan qian
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 1: January 2014
Publisher : Institute of Advanced Engineering and Science

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Abstract

In this paper, we propose a method to analyze the shortest path finding between two nodes in complex networks. In this method, we first find that single Brownian particle follows the shortest path between source node and destination node in the probability of where denotes the shortest path steps between two nodes. To be compared with single particle utilization, then we specially analyze the multiple particles. We compute the probability of particles’ taking the shortest path between and when particles starts simultaneously from the source and head to the destination as . It’s very clear that there must be particles taking the shortest path to arrive at the destination in the multiple particles environment. And with the number of increasing, the arriving probability first arise and then drop down rapidly until to zero. In the end, we make the experiments and confirm our theoretical analysis. Our results would provide valuable usage for some applications such as finding the optimal routing in wireless sensor networks. DOI : http://dx.doi.org/10.11591/telkomnika.v12i1.3071
Hybrid Feature Selection Based on Improved GA for the Intrusion Detection System Shu-xin Zhu; Bin Hu
Indonesian Journal of Electrical Engineering and Computer Science Vol 11, No 4: April 2013
Publisher : Institute of Advanced Engineering and Science

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Abstract

High dimensionality is one of the most troublesome difficulties encountered in intrusion detection system analysis and application. For high dimension data, feature selection not only can improve the accuracy and efficiency of classification, but also discover informative subset. Combining Filter type and Wrapper type characteristics, this paper proposes a hybrid type method for feature selection using a improved genetic algorithm contained reward and punishment mechanism. The mechanism can guarantee this algorithm rapid convergence on approximate global optimal solution. According to the experimental results, this algorithm performs well and it's time complexity is low. Keywords: intrusion detection system; genetic algorithm(GA); Feature selection; Mutual information; hybrid type.DOI: http://dx.doi.org/10.11591/telkomnika.v11i4.1823
Co-Authors huan yan qian jia li xu Shu-xin Zhu