Title :
Representative information models for monitoring and control in the conditions of uncertainty
Author :
Lazarev, Victor L.
Author_Institution :
ITMO Univ., St. Petersburg, Russia
Abstract :
In the paper are observed the issues of information models synthesis based on the "entropy" approach. There are presented variants of models adapted to different situations. Also are designed recommendations and the criteria for specific options selection. The proposed models are based on the standard statistical characteristics of analyzed parameters usage, and are compact and convenient for solving various problems of monitoring and control, especially in the conditions of uncertainty.
Keywords :
entropy; statistical analysis; control; entropy approach; information models synthesis; monitoring; options selection; parameters usage; representative information models; statistical characteristics; uncertainty conditions; Adaptation models; Analytical models; Entropy; Estimation; IP networks; Monitoring; Uncertainty; conditions of uncertainty; control; entropy potential; information models; monitoring;
Conference_Titel :
Soft Computing and Measurements (SCM), 2015 XVIII International Conference on
Conference_Location :
St. Petersburg
Print_ISBN :
978-1-4673-6960-2
DOI :
10.1109/SCM.2015.7190408