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Evidence-fuzzy system for human concurrent activities recognition

机译:人类同时活动识别的证据模糊系统

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Activity recognition is an important task which can be applied to many real-life problems in pervasive computing. In this work, we propose concurrent activities recognition system based on two layers of inference. The first layer develops a framework for dealing with fusion system through merging different sources of information using evidence theory. The second layer proposes a decision framework under the fuzzy logic formalism. Our experimental results suggest that the fuzzy logic method for the plausibility combinations at the decision level is the best for activities in progress simultaneously but not necessarily involving the user's interaction at the same time steps. It yields high accuracy of 79.7%, regarding experimental results.
机译:活动识别是一项重要任务,可以应用于普适计算中的许多现实生活中的问题。在这项工作中,我们提出了基于两层推理的并发活动识别系统。第一层通过使用证据理论合并不同的信息源,开发了一个用于处理融合系统的框架。第二层提出了模糊逻辑形式主义下的决策框架。我们的实验结果表明,在决策级别上针对合理性组合的模糊逻辑方法最适合同时进行的活动,但不一定要同时涉及用户的交互。就实验结果而言,它的准确度高达79.7%。

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