态势感知计算系统中的不确定性处理

Chunchen Liu, Da-you Liu, Sheng-sheng Wang
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引用次数: 7

摘要

情境感知是上下文感知的一种更全面、更有前景的版本,是使环境智能系统更具适应性和智能化的关键。情境感知计算系统需要表示情境信息,根据情境识别相关情境,然后根据情境采取相应的行动。然而,在这些过程中需要处理两种主要的不确定性:上下文或情境的语义可能是模糊的;环境本身就是不完美的。本文提出了一种创新的不确定环境下态势感知计算框架,利用基于模糊描述逻辑的模糊本体对情境进行建模,提出了几种新的算法来识别考虑不确定性的实体情境,开发了一种基于模糊逻辑和模糊学习技术的模糊系统来主动、自动地进行决策。此外,我们还开发了智能家居应用的原型,实验结果表明我们的新技术是可行和有效的。
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Dealing with Uncertainty in Situation-aware Computing System
Situation awareness is a more holistic and promising version of context awareness, which is a key to making Ambient Intelligence systems more adaptive and intelligent. A situation-aware computing system needs to represent context information, identify relevant situations based on the context, and then take appropriate actions according to situations. However, two main kinds of uncertainty need to be handled in these processes: the semantic of context or situation may be fuzzy; context is inherently imperfect. This paper proposes an innovative framework for carrying out situation-aware computing under uncertainty where fuzzy ontology based on fuzzy description logic is used to model context, several new algorithms are proposed to identify entities’ situations considering uncertainty, a fuzzy system based on fuzzy logic and fuzzy learning techniques is developed to make decisions proactively and automatically. In addition, we develop a prototype of smart home application, experimental results from it show that our new technologies are feasible and effective.
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