基于数据挖掘和模糊聚类的计算机软件工程项目自动化管理研究

Li Zhang
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引用次数: 0

摘要

. 计算机软件工程项目自动化管理的顺利实施,对促进计算机软件开发的更快发展,进一步推动计算机软件工程的发展起到了重要的作用。在实现工程自动化管理的过程中,引入了数据挖掘技术和方法,提出了一种基于数据挖掘的计算机辅助质量功能配置模型。开发了数据挖掘工具,建立了产品用户需求和过程质量选择分解模型。同时,建立了模糊聚类和灰色理论算法的数据挖掘模型,并对相关应用实例进行了分析。目前,所有的效度判别方法都不具有绝对的优势,都需要针对特定的数据集进行适应和选择。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research on Computer Software Engineering Project Automation Management based on Data Mining and Fuzzy Clustering
. The smooth implementation of automation management of computer software engineering projects has played an important role in promoting the faster development of computer software development and further promoting the development of computer software engineering. In the process of realizing automation management of project, data mining technology and method are introduced, and a computer aided quality function configuration model based on data mining is proposed. The data mining tool was developed, and the model for product user demand and process quality selection decomposition was established. At the same time, the data mining model of fuzzy clustering and grey theory algorithm was established, and related application examples were analyzed. At present, all methods of validity discrimination do not have absolute advantages, and all need to be adapted and selected for specific data sets.
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