Characterization of Meteorological Drought Using Monte Carlo Feature Selection and Steady-State Probabilities

Figure 2

Flowchart of the RCAMD. In starting the RCAMD, three varying indices are calculated for the drought analysis. These calculated indices are further used for the drought classification. The drought classification criteria implemented in several publications [115] and Niaz et al. [76, 96, 97, 99] are used in the current research. In the next step, the MCFS is applied using three drought indices (SPI, SPEI, and SPTI) for selecting important stations. Consequently, the MCFS chooses an important meteorological station for each drought index. The use of MCFS input enables the RCAMD to accumulate information from various stations comprehensively. Moreover, in RCAMD, SSP is employed to disseminate weights for numerous drought categories over various stations and indices. The SSP mainly employs to characterize the new vector of drought categories. Conclusively, the resultant data mining vector based on MCFS and SSP in RCAMD provides a comprehensive information from several stations and indices.