The paper considers the issues of implementation and application of intelligent computing on the basis of cognitive and event modeling in research on energy security. The authors suggest a two-level information technology for the research. The first level suggests a situation analysis using the intelligent computing techniques. The analysis results are then used to choose rational variants of energy development in Russia (or its regions). At the second level these variants are computed with the multi-agent software INTEC-M. Transition from the first to the second level is automated by the tools of deductive program synthesis, that are based on declarative descriptions, i.e. formulae of restricted predicate calculus, and representation of input data by XML files. Cognitive and event modeling is considered in more detail. The examples of cognitive and event models are presented. The structure of a knowledge space is developed to support the intelligent computations. The knowledge space includes ontological models, databases of cognitive and event models, and the database on the cases of energy emergency situations. The authors developed the CogMap and EventMap tools to support cognitive and event modeling on the basis of common graphical environment GirModeling, and the expert system “Emergency”. The tools and expert system that support the knowledge base on energy emergencies are integrated within the intelligent IT environment. The research presented in the paper was partially supported by the grant of Presidium of RAS No. 2.2-2012 and grants of Russian Foundation of Basic Research No. 10-07-00264, No. 11-07-00192, No. 11-07-00245, and No. 12-07-00359.
The paper considers the issues of implementation and application of intelligent computing on the basis of cognitive and event modeling in research on energy security. The authors suggest a two-level information technology for the research. The first level suggests a situation analysis using the intelligent computing techniques. The analysis results are then used to choose rational variants of energy development in Russia (or its regions). At the second level these variants are computed with the multi-agent software INTEC-M. Transition from the first to the second level is automated by the tools of deductive program synthesis, that are based on declarative descriptions, i.e. formulae of restricted predicate calculus, and representation of input data by XML files. Cognitive and event modeling is considered in more detail. The examples of cognitive and event models are presented. The structure of a knowledge space is developed to support the intelligent computations. The knowledge space includes ontological models, databases of cognitive and event models, and the database on the cases of energy emergency situations. The authors developed the CogMap and EventMap tools to support cognitive and event modeling on the basis of common graphical environment GirModeling, and the expert system “Emergency”. The tools and expert system that support the knowledge base on energy emergencies are integrated within the intelligent IT environment. The research presented in the paper was partially supported by the grant of Presidium of RAS No. 2.2-2012 and grants of Russian Foundation of Basic Research No. 10-07-00264, No. 11-07-00192, No. 11-07-00245, and No. 12-07-00359.
The paper introduces the concept of aggregation of indicators as a mapping of a set of their values into a single numer-ical value (named aggregate) using a bounded non-decreasing and non-constant function U(X). The concepts of aggre-gation by necessity and sufficiency are introduced and it is shown that there are no other options for such aggregation. The properties of aggregation by necessity and sufficiency are investigated. The concepts of value and utility of a sub-set of indicators as measures of its necessity and sufficiency are introduced. The value is related to the decrease amount of aggregate when minimizing the indicators included in the corresponding subset, and the utility is related to the value of the aggregate when only these indicators take the maximum value. It is noted that the properties of aggre-gated systems (systems for each component of which there is an aggregate) are determined by the laws of aggregation among other things. For example, that each aggregated system has a core, i.e. a subset of components (subsystems and functional elements), the functionality of which determines the functionality of the system as a whole and this is not due to the nature of the system, but only to the fact that it is aggregated.
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