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An incremental Granular Network for data modeling in software engineering

机译:用于软件工程中数据建模的增量式粒度网络

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In this paper, we propose an incremental method of Granular Networks (GN) to construct conceptual and computational platform of Granular Computing (GrC). The essence of this network is to describe the associations between information granules including fuzzy sets formed both in the input and output spaces. The context within which such relationships are being formed is established by the system developer. Here information granules are built using Context-driven Fuzzy Clustering (CFC). This clustering develops clusters by preserving the homogeneity of the clustered patterns associated with the input and output space. The experimental results on well-known software module of Medical Imaging System (MIS) revealed that the incremental granular network showed a good performance in comparison to other previous literature.
机译:在本文中,我们提出了一种渐进式的颗粒网络(GN)方法,以构建颗粒计算(GrC)的概念和计算平台。该网络的本质是描述包括在输入和输出空间中形成的模糊集在内的信息颗粒之间的关联。由系统开发人员建立在其中形成这种关系的上下文。在这里,信息粒度是使用上下文驱动的模糊聚类(CFC)构建的。该聚类通过保持与输入和输出空间关联的聚类模式的同质性来发展聚类。在医学成像系统(MIS)的知名软件模块上的实验结果表明,与以前的其他文献相比,增量粒度网络显示出良好的性能。

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