Identification of influential weather parameters and seasonal drought prediction in Bangladesh using machine learning algorithm.

ABSTRACT: Droughts pose a severe environmental risk in countries that rely heavily on agriculture, resulting in heightened levels of concern regarding food security and livelihood enhancement. Bangladesh is highly susceptible to environmental hazards, with droughts further exacerbating the precarious situation for its 170 million inhabitants. Therefore, we are endeavouring to highlight the identification of the relative importance of climatic attributes and the estimation of the seasonal intensity and frequency of droughts in Bangladesh. With a period of forty years (1981-2020) of weather data, sophisticated machine learning (ML) methods were employed to classify 35 agroclimatic regions into dry or wet conditions using nine weather parameters, as determined by the Standardized Precipitation Evapotra

SUBMITTER: Al Mamun MA 

PROVIDER: S-EPMC10767098 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature