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- W2548897277 abstract "It is well-known that the correct diagnosis for wireless sensor network can avoid the paralysis of entire systems. Here, fault diagnosis for wireless sensor network based on genetic-support vector machine is presented in the paper. In SVM, inappropriate training parameters can lead to over-fitting or under-fitting. Thus, genetic algorithm is used to select the appropriate training parameters of support vector machine. Genetic algorithm is a kind of evolutionary computing algorithm, which has strong global search ability. In the experiments, 60 state samples of wireless sensor network are employed to study the diagnosis ability of genetic-support vector machine. The experimental results show that the diagnosis accuracy of the genetic-support vector machine model is higher than that of the support vector machine model." @default.
- W2548897277 created "2016-11-11" @default.
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- W2548897277 date "2011-12-01" @default.
- W2548897277 modified "2023-09-25" @default.
- W2548897277 title "Fault diagnosis for wireless sensor network based on genetic-support vector machine" @default.
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- W2548897277 doi "https://doi.org/10.1109/iccsnt.2011.6182520" @default.
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