Examples of a cognitive forecasting system are defined. In an example, the system receives a forecasting requirement from a user. The system obtains parameter data from a plurality of data sources associated with the forecasting requirement and identify a parameter set therein. The system implements an artificial intelligence component to sort the parameter data into a plurality of data domains and identify a set of preponderant data domains therein. The system may update the preponderant data domains based on a modification in the plurality of data domains. The system may establish a forecasting model corresponding to the forecasting requirement by performing a cognitive learning. The system may update the forecasting model corresponding to the update in the parameter data. The system may generate a forecasting result corresponding to the forecasting requirement. The system may generate the cognitive forecasting model that may account for real time fluctuations in the data. (nC 4 Q) C-j ) ('2 C,- CI0 ('2, i 11Q m/o c 0' .- ~ _0 E D' + ' 0 DU U) ('_ a CU a (.0 a) 00a)( y) o U) U)~0 0)~-U a0 0- 0 U) a' J u)0 aoa)u o CCL _0 E Ej 0-
COGNITIVE FORECASTING