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Approach of context-aware computing with uncertainty for ubiquitous active service

机译:普遍存在的主动服务不确定性的上下文感知计算方法

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As we know,context-aware computing with uncertainty is an important part of Pervasive Computing with uncertainty,which includes three aspects: obtaining of context information with uncertainty,modeling and fusing of context information with uncertainty,management of context information with uncertainty.Among these,fusing of context information with uncertainty is the most important.Because multi-source evidence context-aware information with uncertainty is dynamic and changing randomly,in order to ensure the QoS of different application fields based on pervasive computing,we modified the fusion method of evidence information after considering context’s reliability,time-efficiency and relativity,which has improved the classic combination rule of D-S Evidence Theory when used in the pervasive computing paradigm and overcome its shortcoming.All these suggested technologies have been successfully integrated and demonstrated in our project,where including context-aware computing by fusing of dynamic multi-source evidence information with uncertainty.The efficiency of our researches has been tested by application practice and validation of the demo.
机译:众所周知,具有不确定性的上下文感知计算是具有不确定性的普适计算的重要组成部分,包括三个方面:具有不确定性的上下文信息的获取,具有不确定性的上下文信息的建模和融合,具有不确定性的上下文信息的管理。由于不确定性的多源证据上下文感知信息是动态且随机变化的,为了确保基于普适计算的不同应用领域的QoS,我们修改了融合方法。考虑了上下文的可靠性,时间效率和相对性的证据信息,改进了DS证据理论在普适计算范式中使用的经典组合规则,克服了其缺点。所有这些建议技术已在我们的项目中成功集成和演示,通过融合o包括上下文感知计算f具有不确定性的动态多源证据信息。我们的研究效率已通过应用实践和演示验证得到了验证。

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