Intelligent Computing on the Basis of Cognitive and Event Modeling, and Its Application in Energy Security Research

Intelligent Computing on the Basis of Cognitive and Event Modeling, and Its Application in Energy Security Research

L. V. Massel (Energy Systems Institute, Siberian Branch of the Russian Academy of Sciences, Russia), V. L. Arshinsky (Energy Systems Institute, Siberian Branch of the Russian Academy of Sciences, Russia) and A. G. Massel (Energy Systems Institute, Siberian Branch of the Russian Academy of Sciences, Russia)
DOI: 10.4018/978-1-5225-1671-2.ch024
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Abstract

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.
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Knowledge Space For Intelligent Computing

A knowledge space is used to support the intelligent computing. The space is supported by the intelligent IT environment (Figure 1). Ontological models of knowledge, or ontologies (Gruber, 1993; Gavrilova & Khoroshevsky, 2001), that reflect the main concepts of subject domain and relations among them are used for construction of cognitive and event models (Massel, 2010). Descriptions of energy emergencies that are contained in the knowledge base of the expert system “Emergency” are used to identify the emergency situations that occur most frequently and reveal typical threats to energy security that are modeled with cognitive maps. In turn the cognitive maps can be used as initial to construct event models of development and consequences of energy emergency situations. The ontological models are constructed using the typical tools, namely, CmapTools or Protégé. The other knowledge bases are supported by the author software tools.

Figure 1.

Knowledge space supported by the intelligent IT environment

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Cognitive Modeling

Cognitive modeling is taken to mean construction of cognitive models or, in other words, cognitive maps (oriented graphs) in which vertices correspond to factors (concepts) and edges – to the ties between the factors (positive or negative), depending on the character of cause-effect relation (Trakhtengerts, 1998). The authors use cognitive modeling for situation analysis (Pospelov, 1986; Makagonova, Massel & Bakhvalov, 2008; Massel, 2011) of the energy security problem and for modeling of energy security threats (Massel, 2009) which imply unfavorable events for the energy sector that are grouped into seven types of threats: technogenic, economic, natural, sociopolitical, external economic, external political as well as those caused by imperfect management (administrative-judicial). Figure 2 shows a cognitive model of a natural threat (cold snap).

Figure 2.

A cognitive map of a natural threat (cold snap)

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