A parametric model for fusing heterogeneous fuzzy data
A parametric model for fusing heterogeneous fuzzy data
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DOI：
10.1109/91.531770
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发表时间：
1996-08-01
影响因子：
11.9
通讯作者：
Pedrycz, W
中科院分区：
文献类型：
--
作者：
Hathaway, RJ;Bezdek, JC;Pedrycz, W
提出的是一个模型，集成了三种数据类型（数字，间隔和语言评估）。这三种类型的数据来自各种传感器。传感器融合模型的一个目标是为数据集成、处理和解释提供一个通用框架。这就是我们的模型所做的。我们使用一小组人工数据来说明如何不同的问题，如特征分析，聚类，聚类有效性，和原型分类器设计凸轮都制定和攻击标准的方法，一旦数据被转换为我们的模型的广义坐标，重新参数化对计算输出的影响进行了讨论。数值例子表明，所提出的模型提供了一种自然的方法来处理涉及混合数据类型的问题。
Presented is a model that integrates three data types (numbers, intervals, and linguistic assessments). Data of these three types come from a variety of sensors. One objective of sensor-fusion models is to provide a common framework for data integration, processing, and interpretation. That is what our model does. We use a small set of artificial data to illustrate how problems as diverse as feature analysis, clustering, cluster validity, and prototype classifier design cam all be formulated and attacked with standard methods once the data are converted to the generalized coordinates of our model, The effects of reparameterization on computational outputs are discussed. Numerical examples illustrate that the proposed model affords a natural way to approach problems which involve mixed data types.