Application of Systematic Data Mining for Prediction of Biological Quality Indices

Uliana Bakhtina, D. Fleischer, Kai Jannaschk
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Abstract

Data mining is not only a simple application of an algorithm on the data set. It is rather a systematic approach that is absolutely necessary, if we want to obtain useful and meaningful patterns from data. This paper shows how the usage of systematic data mining can help to simplify the first determination of the quality of marine habitats in the western Baltic Sea. The Benthic Quality Index (BQI) has been introduced within the European Union Water Framework Directive to assess the quality of marine habitats. The index is based on sensitivity/tolerance classification and quantitative information on the composition of soft-bottom macro fauna. The calculation of the index is based on the exact designation of the found taxa.
系统数据挖掘在生物质量指标预测中的应用
数据挖掘不仅仅是一种算法在数据集上的简单应用。如果我们想从数据中获得有用和有意义的模式,这是一种绝对必要的系统方法。本文展示了系统数据挖掘的使用如何有助于简化对波罗的海西部海洋栖息地质量的首次确定。底栖生物质量指数(BQI)已在欧洲联盟水框架指令中引入,以评估海洋栖息地的质量。该指数基于软底大型动物群组成的敏感性/耐受性分类和定量信息。索引的计算基于所发现分类群的确切名称。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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