APPLICATION OF DATA MINING IN THE ECOLOGICAL ANALYSIS OF THE IMPACT OF BACTERIAL COMMUNITIES IN DIFFERENT RESERVOIRS

I. Radojević, A. Ostojić, N. Stefanović
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Abstract

Using data mining techniques, this study analyzes the influence and dependance of bacterial communities that are determined in routine monitoring of open water quality status, such as heterotrophic bacteria (psychrophiles and mesophiles). The SeLaR database was used, which, in addition to various studies of integrated data related to the reservoirs of Serbia, is the basis for advanced data analysis – utilizing statistical methods and data mining. Data for reservoirs with different morphometric qualities, different positions, trophic status, and dominant bacterial community were analyzed. In this research, classification, and analysis of influential parameters, as well as scenario analysis was applied. The results indicate that a designed data mining system can analyze the state and influence of bacterial communities with different parameters that are determined both in standard routine analysis, and in some more specialized studies. This study showed that designed data mining system can serve as flexible, effective, and practical tool for monitoring water quality using bacterial communities in reservoirs.
数据挖掘在不同水库细菌群落影响生态分析中的应用
利用数据挖掘技术,本研究分析了开放水质状态常规监测中确定的细菌群落的影响和依赖性,如异养细菌(嗜冷菌和嗜中菌)。使用了SeLaR数据库,该数据库除了对与塞尔维亚储层有关的综合数据进行各种研究外,还是利用统计方法和数据挖掘进行高级数据分析的基础。对不同形态质量、不同位置、不同营养状况、不同优势菌群的水库资料进行了分析。在本研究中,采用了影响参数的分类和分析,以及情景分析。结果表明,所设计的数据挖掘系统可以分析在标准常规分析和一些更专业的研究中确定的不同参数下细菌群落的状态和影响。研究表明,所设计的数据挖掘系统可以作为一种灵活、有效、实用的工具,用于利用水库细菌群落监测水质。
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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