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Article title METHOD OF THE SELECTION OF EFFECTIVE CONTROLS IN FUZZY COGNITIVE MODELS REPRESENTED AS DIRECTED WEIGHTED GRAPHS
Authors A.N. Tselykh, V.S. Vasilev, L.A. Tselykh, S.A. Barkovskii
Section SECTION I. AUTOMATION AND CONTROL
Month, Year 05, 2016 @en
Index UDC 004.891.2
DOI
Abstract In this article, we present a new method of selection effective controls which is based on the transitive power influence transmission between the nodes in the directed weighted graphs with cause-and-effect relationships. These graphs can be a cognitive model of socio-economic system. The influence will be determined from the solution of linear systems. The influences will be determined from the solutions generated by System of Linear Algebraic Equations (SLAE). To solve the problem of identification and selection of effective controls, we introduce the theory of effective controls in this article. This approach is based on the provisions of the general systems theory and systems analysis in the annex to the management of socio-economic systems. This approach is based on the provisions of the general systems theory and systems analysis in the annex to the socio-economic systems management. For its presentation we will determine definitions of certain vertices state metrics, reflecting the impact of components of effective controls in the system. The solution problem for the searching of optimal control that turns to the problem of maximizing a quadratic form, which ensures its validity (the existence of the solutions, the possibility of the solutions and uniqueness of the solution), calculating a real, rather than complex domain and independent from conditions of stability. Based on the theory of effective controls, vertices metrics are offered that evaluate and measure the ability of efficient controls in accordance to the measuring of the growth factor of a model during control influence.

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Keywords Directed weighted graphs; components of effective controls; functional optimization on graphs; SLAE decision on graphs; fuzzy cognitive maps
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