A Method of Interval Prediction based on Logical Regularities

G.S. Lbov, M.K. Gerasimov, and G.L. Polyakova (Russia)


Modelling, interval prediction, logical regularity, experts


In this work, certain problems related to construction of probabilistic logical models for interval prediction are considered. These models are deļ¬ned as sets of logical regularities, i.e. sets of statements with high probabilistic abilities. Methods of obtaining logical regularities based on both analysis of multidimensional samples and anal ysis of statements from different experts are proposed. The methods were tested on astrophysical, climatic data, and tick-borne encephalitis indices. Results show the ef fectiveness of the methods in obtaining cause-effect rela tions.

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