Evolving Simulation Modeling : Calibrating SLEUTH Using a Genetic Algorithm
Evolving Simulation Modeling : Calibrating SLEUTH Using a Genetic Algorithm
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不断发展的仿真建模：使用遗传算法校准 SLEUTH
DOI：
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发表时间：
2011
期刊：
影响因子：
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通讯作者：
K. Clarke
中科院分区：
文献类型：
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作者：
M. Clarke;K. Clarke
随着我们的环境中不断集成各种普及计算设备以及用户移动性的不断增加，移动系统和服务有必要具有上下文感知能力。向用户介绍相关上下文是上下文感知系统的主要属性，尤其是空间相关上下文。大多数情况下，随着情况逐渐发生变化，人们能够看到一些相关物体的距离并没有明显的界限。上下文似乎没有清晰的边界，一侧为真，另一侧为假。另一方面，每个上下文和移动用户在城市网络中都有一个影响区间。因此，对上下文和移动用户应用模糊空间区间并定义它们的空间关系可以有效地对空间相关性参数进行建模。本文的主要贡献是引入模糊区间代数来建模上下文感知系统中的空间相关性。所提出的算法在上下文感知的旅游指南系统中实现。实验结果表明，该算法能够准确检测空间上下文。
With an ongoing variety of pervasive computing devices integrated in our environment and an increasing mobility of users, it is necessary for mobile systems and services to be context-aware. Introducing relevant contexts to the user is the main properties of context-aware systems especially spatial relevant contexts. Most often as situations change gradually, there is no sharp boundary about how far one can see some relevant objects. It seems that contexts do not have crisp borders where they are true on one side but false on the other side. On the other hand, every context and mobile user has an influence interval in an urban network. So applying fuzzy spatial inervals for contexts and mobile users and defining their spatial relationships could effectively model spatial relevancy parameter. The main contribution of this paper is introducing fuzzy interval algebra for modeling spatial relevancy in context-aware systems. The proposed algorithm is implemented in a context-aware tourist guide system. The experimental results showed that the algorithm could accurately detect the spatial contexts.