论文标题
使用级联模型对喀斯特地区微生物海水质量分类的预测建模
Predictive modeling of microbiological seawater quality classification in karst region using cascade model
论文作者
论文摘要
在本文中，对克罗地亚里耶卡市的沐浴季节对大肠杆菌海水测量进行了深入分析。在几个测量位置观察到地下水的淹没来源，这可能是大肠杆菌值增加的原因。通常在监测过程中不考虑喀斯特地形的这种特异性，因此提出了一种新颖的测量方法。级联机器学习模型用于基于气象数据来预测沿海水质，这提高了由于很少出现水质降低的测量结果而导致的数据不平衡所致。当前，级联模型被用作滤波器方法，其中未归类为优秀质量的测量需要进一步分析。但是，随着论文提出的改进，级联模型最终可以用作独立方法。
In this paper, an in-depth analysis of Escherichia coli seawater measurements during the bathing season in the city of Rijeka, Croatia was conducted. Submerged sources of groundwater were observed at several measurement locations which could be the cause for increased E. coli values. This specificity of karst terrain is usually not considered during the monitoring process, thus a novel measurement methodology is proposed. A cascade machine learning model is used to predict coastal water quality based on meteorological data, which improves the level of accuracy due to data imbalance resulting from rare occurrences of measurements with reduced water quality. Currently, the cascade model is employed as a filter method, where measurements not classified as excellent quality need to be further analyzed. However, with improvements proposed in the paper, the cascade model could be ultimately used as a standalone method.
