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Exploring an Ichthyoplankton Database from a Freshwater Reservoir in Legal Amazon

机译:在Legal Amazon的淡水水库中探索浮游鱼类数据库

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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:这项研究的目的是使用数据挖掘技术对合法亚马逊河淡水水库浮游鱼类的数据库进行探索性分析。该数据库已经使用统计技术进行了分析,但是这些未发现生物因素和非生物因素之间的关系。 Apriori算法的应用使我们能够生成关联规则,从而了解Tocantins河中鱼类产卵的过程。在这种情况下,我们证明了有效利用数据挖掘来发现生态系统中的模式和过程,并建议生态学家经常使用的统计方法可以与数据挖掘技术结合使用以产生假设。

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