Analyzing the relation between heart rate, problem behavior, and environmental events using data mining system LERS

Author(s):  
R.L. Freeman ◽  
J.W. Grzymala-Busse ◽  
L.A. Riffel ◽  
S.R. Schroeder
2021 ◽  
Author(s):  
Ivana Radojević ◽  
◽  
Aleksandar Ostojić ◽  
Nenad Stefanović

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.


2015 ◽  
Vol 42 (6Part14) ◽  
pp. 3364-3364
Author(s):  
A Dhabaan ◽  
X Jiang ◽  
E Schreibmann ◽  
E Elder

2001 ◽  
Vol 24 (3) ◽  
pp. 222-231 ◽  
Author(s):  
Chi Zhou ◽  
P.C. Nelson ◽  
Weimin Xiao ◽  
T.M. Tirpak ◽  
S.A. Lane

1998 ◽  
Vol 21 (3) ◽  
pp. 163-185 ◽  
Author(s):  
Johnny S.K. Wong ◽  
Rishi Nayar ◽  
Armin R. Mikler

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