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Exploring an Ichthyoplankton Database from a Freshwater Reservoir in Legal Amazon

机译:从合法亚马逊的淡水储层探索ICHThyoplankton数据库

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The purpose of this study is to use data mining techniques for the exploratory analysis of a database of ichthyoplankton samples from a freshwater reservoir in Legal Amazon. This database has already been analyzed using statistical techniques, but these did not find a relationship between biotic and abiotic factors. The application of the Apriori algorithm allows us to generate association rules that yield an understanding of the process of fish spawning in Tocantins River. In this case, we demonstrate the effective use of data mining for the discovery of patterns and processes in ecological systems, and suggest that statistical methods often used by ecologists can be coupled with data mining techniques to generate hypotheses.
机译:本研究的目的是利用数据挖掘技术来分析来自法律亚马逊的淡水储层的ICHThyoplankton样本数据库。该数据库已经使用统计技术进行了分析,但这些数据库没有找到生物和非生物因素之间的关系。 APRiori算法的应用允许我们生成关联规则,从而了解在Tocantins河中产生的鱼类流程的过程。在这种情况下,我们展示了数据挖掘的有效利用生态系统中的模式和过程,并表明生态学家经常使用的统计方法可以与数据挖掘技术耦合以产生假设。

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