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A Novel Range-Free Grid Localization Algorithm Based on Support Vector Machine in Wireless Multimedia Sensor Networks

机译:一种基于支持向量机的无线多媒体传感器网络的无栅网本地化算法

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Wireless multimedia sensor networks (WMSN) play an important role in many applications. The location of sensor nodes is the key to achieving sensor data effectively. In this paper, we use multi-category support vector machine (multi-category SVM) to divide the whole network into grids to resolve a localization problem in WMSN. By multi-category SVM localization model, we can predict the location of new nodes, and the result shows that this method can improve the accuracy of localization compared with the same kind.
机译:无线多媒体传感器网络(WMSN)在许多应用中发挥着重要作用。传感器节点的位置是有效实现传感器数据的关键。在本文中,我们使用多类别支持向量机(多类SVM)将整个网络划分为网格以解决WMSN中的本地化问题。通过多类SVM定位模型,我们可以预测新节点的位置,结果表明,该方法可以提高定位的准确性与相同类型相比。

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