Authors : Gennadiy V. Averin, Igor S. Konstantinov, Anna V. Zviagintseva and Oksana A. Tarasova
Abstract: The topical issues related to the problem of multidimensional data modeling that characterize the processes and the system state of different nature. The physical and chemical, engineering, manufacturing, biological and socio-economic systems are considered the quantitative information about which may be presented as the arrays of tabular-time data. Each table of such an array has the structure “objects and settings” and many tables are ordered in time. The principles of creation and relational-field approach of multi-dimensional data model development are proposed for such information arrays. The peculiarity of the approach is the use of data presentation idea as a hypothetical solid information environment and the application of existence hypothesis concerning an information measure for a comprehensive assessment of tabular data array in the form of joint event probability field associated with the simultaneous observation of object parameters. It is also shown that using the hypothesis characterizing the features of data changes over time, you may reduce the initial modeling problems to the solution of mathematical physics equations. The obtained results enable to develop the methods of data modeling for the databases characterizing the condition and behavior of certain system classes.
Gennadiy V. Averin, Igor S. Konstantinov, Anna V. Zviagintseva and Oksana A. Tarasova, 2015. The Development of Multi-Dimensional Data Models Based on the Presentation of an Information Space as a Continuum. International Journal of Soft Computing, 10: 458-461.