The invention relates to the technical field of space-time prediction, in particular to a
brucellosis space-time prediction method and
system based on
artificial intelligence, and the method comprises the following steps: obtaining case information, calculating an incidence relation, extracting a path sequence, screening a trend direction, and matching a new case to generate prediction data. According to the method, continuous identification of a propagation path is realized by constructing a propagation incidence relation between cases and introducing a spatial
directivity index, a non-trend propagation process is screened out through an angle average value and a variance,
spatial consistency of path screening is enhanced, and through joint matching of spatio-temporal characteristics of newly-added cases and an existing propagation trend, the propagation path screening efficiency is improved. The sensitivity of prediction to the trend attribution of a new case is improved, the spatial
directivity of a potential
disease area is enhanced through reverse projection of a trend path and area positioning drop point
frequency analysis, and through linkage
processing of multi-level path extraction, trend judgment and area coding, the probability of occurrence of the new case is lowered. And the capturing capability of the prediction data on the propagation and evolution characteristics of the
brucellosis is improved.