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Sequential Classifier Combination for Pattern Recognition in Wireless Sensor Networks

机译:无线传感器网络中模式识别的顺序分类器组合

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摘要

In the current paper we consider the task of object classification in wireless sensor networks. Due to restricted battery capacity, minimizing the energy consumption is a main concern in wireless sensor networks. Assuming that each feature needed for classification is acquired by a sensor, a sequential classifier combination approach is proposed that aims at minimizing the number of features used for classification while maintaining a given correct classification rate. In experiments with data from the UCI repository, the feasibility of this approach is demonstrated.
机译:在本文中,我们考虑了无线传感器网络中的对象分类任务。由于电池容量的限制,最大限度地降低能耗是无线传感器网络中的主要问题。假设通过传感器获取分类所需的每个特征,则提出了一种顺序分类器组合方法,其目的是在保持给定正确分类率的同时,将用于分类的特征数量最小化。在使用UCI存储库中的数据进行的实验中,证明了这种方法的可行性。

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