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

1st International Conference on Chemo and BioInformatics, ICCBIKG  2021, (186-189)

AUTHOR(S) / АУТОР(И): Ivana Radojević, Aleksandar Ostojić, Nenad Stefanović

E-ADRESS / Е-АДРЕСА: ivana.radojevic@pmf.kg.ac.rs, aleksandar.ostojic@pmf.kg.ac.rs, nenad@pmf.kg.ac.rs

Download Full Pdf   

DOI: 10.46793/ICCBI21.186R

ABSTRACT / САЖЕТАК:

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.

KEY WORDS / КЉУЧНЕ РЕЧИ:

data mining; reservoirs; bacterial community; heterotrophs; classification; influential parameters, scenario analysis.

REFERENCES / ЛИТЕРАТУРА:

  • Boyacioglu, H. Boyacioglu, Surface Water Quality Assessment by Environmetric Methods. Environmental Monitoring and Assessment, 131 (2007) 371-376.
  • Kumar, J Alameda, P. Bajcsy, M. Folk, M. Markus, Hydroinformatics: Data Integrative Approaches in Computation. Analysis and Modeling. CRC Press, (2006) 534 pp.
  • C. Ogwueleka, F.N. Ogwueleka, Data mining application in predicting Cryptosporidium spp. oocysts and Giardia spp. cysts concentrations in rivers. Journal of Engineering Science and Technology, 5 (2010) 342-349.
  • И.Д. Радојевић, Микробиолошки аспекти примене информационих система у мониторингу акумулација и језера, Докторска дисертација, Природно-математички факултет, Универзитет у Крагујевцу, (2012) 218
  • Harts, Microsoft Office 2007 Bussines Intelligence, McGraw_Hill, (2008). ISBN-13: 978- 0071494243; ISBN-10: 0071494243.