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Data mining techniques for water ecotoxicity classification for application on water resources management

机译:水生态毒性分类数据挖掘技术在水资源管理中的应用

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摘要

Among the various forms of action that promote sustainability, technological innovation can be considered one of the most important. This paper applied data mining techniques to discover knowledge in the field of water quality monitoring data, providing useful and relevant support for decision-making in environmental management systems. At the current stage of research, a predictive modelling technique, known as rule-based classification, was used to find rules that can, based on the values of certain chemical parameters, predict the ecotoxicity level of a water sample. We used data from water analyses from main water bodies of Sao Paulo state in Brazil, from 2005 to 2010. We expect to get a reliable, fast and effective way to predict the ecotoxicity levels of water in rivers, lakes and reservoirs based on analyses of chemical parameters, or indicate the complementarity of these measurements for optimisation of monitoring networks and the consequent improvement natural resources management.
机译:在促进可持续性的各种行动形式中,技术创新可以被认为是最重要的行动之一。本文应用数据挖掘技术来发现水质监测数据领域的知识,为环境管理系统的决策提供有用和相关的支持。在目前的研究阶段,一种预测性建模技术(称为基于规则的分类)用于查找可以基于某些化学参数的值预测水样品的生态毒性水平的规则。我们使用了巴西圣保罗州主要水体2005年至2010年的水分析数据。我们希望通过对水的分析得出一种可靠,快速而有效的方法来预测河流,湖泊和水库中水的生态毒性水平。化学参数,或表示这些测量值的互补性,以优化监控网络并因此改善自然资源管理。

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