Modeling of Artificial Intelligence

14-20

Authors: Hagop Kechejian, Victor K. Ohanyan, Vardan G. Bardakhchyan

In this paper we calculate the price of the arithmetic average Asian option on several consecutive future contracts. The calculations are made using the method introduced by Curran, and the underlying model for future prices proposed by Andersen. His model describes future prices by Stochastic Differential Equations with several coefficients, which are to be evaluated for each case, generally by model calibration. We use least squares principle to do that, taking the sum of squared differences of real values and the values suggested by model to minimum. Curran’s method is based on the order of geometric and arithmetic means, and to calculate value of options takes expectation of conditional expectation of the considered derivative. Splitting the integral into two parts it evaluates explicitly one of them, and approximates the other. For our case new structure of the options and the underlying assets, requires review of the formulas. In the paper we derive the formulas for this case, and use them for calculating the value of Asian option. In the considered example derivative is based on 4 future contracts with 15, 30, 30, 15 days of engagement in Asian option.

29-38

Authors: Simon Zh. Simavoryan, Arsen R. Simonyan, Elena I. Ulitina, Rafik A. Simonyan, Ellina A. Pilosyan, Nadezhda A. Kornienko

Work is devoted to development of methods of search of an indistinct image of the malefactor on the basis of use of methods of automatic classification. This type of search is used by initial search when the inquiry is set in the form of the description of signs of malicious action. Search is carried out on data from the specialized knowledge base on malicious actions (templates) and the knowledge base on regular situations and values of their admissible characteristics. Methods of automatic classification meet as well other names: objective classification, splitting, taxonomy, diagonalization of matrixes of communication, etc. When using these methods, given about malicious actions, join in the knowledge base as an image (n + 1) member malicious action. After that some algorithm of automatic classification which is carrying out splitting the knowledge base into groups of images of malicious actions "uniform" somewhat is put in action. As result of initial search of an image of the malefactor system the images of malefactors carried by an algorithm of automatic classification in the same group, as an image of the malefactor for whom the image of malicious action is looked for are given. For increase in a noise stability of the procedure of initial search of an indistinct image of the malefactor it is possible to carry out in parallel splitting on various algorithms of automatic classification then as an indistinct image of the malefactor to give association (for increase in completeness of initial search), crossing (for completeness of accuracy), or composition of subsets in which has been carried (n + 1) member an image from the knowledge base.

46-54

Authors: V.Ya. Tsvetkov

The article introduces a new type of management information-intelligent management. The article reveals the content of intellectual management based on the semiotic approach. The article describes the content of the semiotic system as the basis of management. The article introduces a trinitarian model of the information situation. The article describes the static and dynamic components of the semiotic system. The article reveals the relationship between information and situational management. The article describes the content of information intellectual management.