From Catastrophic to Complex System Control of Exercise - The Central Governor Model

2005 ◽  
Vol 37 (Supplement) ◽  
pp. S406
Author(s):  
Timothy D. Noakes
Transport ◽  
2004 ◽  
Vol 19 (2) ◽  
pp. 51-55 ◽  
Author(s):  
Yasaratne Bandara Dissanayake ◽  
Aleksandr Pankov ◽  
Vladimir Shestakov Shestakov

Statistical methods are extensively used in quality control. The method of the application of entropy conception for quality control is proposed. It is based on the use of statistical information about deviations in the operation of a complex system. In the context of this: the structure of the complex system control is considered; the conceptions of controllable and observable systems are introduced. The classification of adverse factor is given influencing upon the system. The example is presented, showing how the application of the proposed method permits to give the evaluation of sources of risks and quality reduction in the complex system.


2012 ◽  
Vol 52 (No. 11) ◽  
pp. 516-521
Author(s):  
A. Veselý

Procedural knowledge is used by experts for complex system control. In this article, the notion of a complex system is taken in a broad sense. It might be a patient cured by a physician specialist, a biotechnological device, a department of some business enterprise etc. The GLIF model was designed in collaboration of American universities for the formalization of medical guidelines, but it can be used for formal representation of any procedural knowledge. The main objective of the GLIF model was to enable computer processing and comparing of medical guidelines. In this, article also a more sophisticated use of procedural knowledge representation by the means of the GLIF model is proposed. The provided data about expert actions are stored into the database, the formalized knowledge represented by the GLIF model can be used for building up sophisticated reminder systems that warn the user if he decides to make an impropriate action. Different kinds of warnings in the reminder system are proposed and their properties are discussed. At the end, also the possibility of using the GLIF model for decision support is discussed. 


2021 ◽  
Vol 106 ◽  
pp. 04004
Author(s):  
Alla Rasputina

Methods for obtaining, analyzing and processing expert information in the system of the agro-industrial complex are of great and ever increasing importance. Moreover, the subsystem of expert information is constantly evolving as a result of the qualitative growth of information and communication technologies and the improvement of the methodological and methodological apparatus of organizing and conducting examinations. Nevertheless, the potential and aggregate possible subsystems of expert information are not used effectively enough due to various reasons, both objective and subjective. The main purpose of the expert information subsystem is to organize and conduct examinations that ensure a high professional level of decision-making in the system of the agro-industrial complex at different levels of management. The research methodology is based on the selective application of system analysis methods aimed at studying complex objects and processes of the agro-industrial complex system, with the predominant use of expert assessment methods. In the process of the first stage of the study of the expert and information subsystem of the agro-industrial complex, based on the method of passive examination in the context of the agricultural digitalization project, a digraph of the structure of the problem field of digitalization was developed, which clearly reflects the interconnections and interactions of individual structural elements of the agro-industrial complex. A scheme for a multistage examination of the problem of digitalization of the regional system of the agro-industrial complex has been developed, an algorithm has been developed for the subsystem of expert information of the agro-industrial complex in the form of a tree-like digraph, reflecting the functional structure of the subsystem. This will allow in the future, with the active use of the developed algorithm for the optimal functioning of the subsystem of expert information of the agro-industrial complex, to ensure high efficiency of the decisions made and the transition to cognitive models of system control.


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