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Biological sequence classification algorithm based on density-aware patterns
HU Yaowei, DUAN Lei, LI Ling, HAN Chao
Journal of Computer Applications    2018, 38 (2): 427-432.   DOI: 10.11772/j.issn.1001-9081.2017071767
Abstract419)      PDF (894KB)(309)       Save
Concerning unsatisfactory classification accuracy and low efficiency of the existing pattern-based classification methods for model training, a concept of density-aware pattern and an algorithm for biological sequence classification based on density-aware patterns, namely BSC (Biological Sequence Classifier), were proposed. Firstly, frequent sequence patterns based on density-aware concept were mined. Then, the mined frequent sequence patterns were filtered and sorted for designing the classification rules. Finally, the sequences without classification were classified by classification rules. According to a number of experiments conducted on four real biological sequence datasets, the influence of BSC algorithm parameters on the results were analyzed and the recommended parameter settings were provided. Meanwhile, the experimental results showed that the accuracies of BSC algorithm were improved by at least 2.03 percentage points compared with other four pattern-based baseline algorithms. The results indicate that BSC algorithm has high biological sequence classification accuracy and execution efficiency.
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Dynamic spectrum access mechanism of multi-users based on restless multi-armed bandit model in cognitive networks
ZHU Jiang HAN Chao YANG Jielei PENG Zhuxun
Journal of Computer Applications    2014, 34 (10): 2782-2786.   DOI: 10.11772/j.issn.1001-9081.2014.10.2782
Abstract373)      PDF (722KB)(426)       Save

Based on the theory of Restless Multi-Armed Bandit (RMAB) model, a novel mechanism of dynamic spectrum access was proposed for the problem that how to coordinate multiple user access multiple idle channels. Firstly, concerning the channel sensing error of the cognitive user being existed in the practical network, the Whittle index policy which can deal with sensing error effectively was derived. In this policy, the users achieved one belief value for every channel based on the historical experience accumulation and chose the channel, which was needed to sense and access, by considering the immediate and future rewards based on the belief values. Secondly, this paper used the multi-bid auction algorithm to deal with the collision among secondary users when they selected the channels to improve the spectrum utilization. The simulation results demonstrate that, in the same environment, the cognitive users with the proposed mechanism have higher throughtput than the mechanism without dealing with sensing error or without multi-bid.

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