Characterization of Meteorological Drought Using Monte Carlo Feature Selection and Steady-State Probabilities
نویسندگان
چکیده
Drought is a creeping phenomenon that slowly holds an area over time and can be continued for many years. The impacts of drought occurrences affect communities environments worldwide in several ways. Thus, assessment monitoring region are crucial reducing its vulnerability to the negative drought. Therefore, comprehensive techniques methods required develop adaptive strategies undertake reduce substantially. For this purpose, study proposes new method known as regional meteorological (RCAMD). Standardized Precipitation Index (SPI), Evapotranspiration (SPEI), Temperature (SPTI) jointly used development RCAMD. Further, RCAMD employs Monte Carlo feature selection (MCFS) steady-state probabilities (SSPs) comprehensively collect information from various stations indices. Moreover, validated on six selected northern areas Pakistan. outcomes associated with provide become initial source bringing more considerations early warning systems.
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ژورنال
عنوان ژورنال: Complexity
سال: 2022
ISSN: ['1099-0526', '1076-2787']
DOI: https://doi.org/10.1155/2022/1172805