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Data Mining Using Cat Swarm Optimization CSO Algorithm

机译:使用CAT群优化CSO算法的数据挖掘

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With the dynamic structures of databases from side and the continuous changes in the stored data in another side it has become necessary using tools and algorithms of data mining. In this paper, the Cat Swarm Optimization CSO algorithm has been used for its effective search and extraction of optimal data. CSO has two modes : tracing mode and seeking mode. This paper has five test reference functions that were used out of twelve. To evaluate the algorithm and determine its relevance to the research, the test results will show that this method has many advantages in prediction, data processing speed, durability, range, and data quality. This paper emphasis that CSO is very effective in the process of data mining.
机译:通过侧面的数据库动态结构和另一侧存储数据的连续变化,它已经使用了数据挖掘的工具和算法。在本文中,CAT Swarm优化CSO算法已被用于其有效的搜索和提取最佳数据。 CSO有两种模式:跟踪模式和寻求模式。本文有五个试验参考功能,二十多次。为了评估算法并确定其与研究的相关性,测试结果将显示该方法在预测,数据处理速度,耐久性,范围和数据质量方面具有许多优点。本文强调CSO在数据挖掘过程中非常有效。

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