ML Based Model Analysis for Regional Fruit and Crop Categorization in Central Asia
Аннотация
Agriculture functions as a fundamental economic sector within Uzbekistan leading to distinct regional effects on land cultivation and tree production. The author investigates the utilization of established ML models to identify fruit and crop classes by analyzing regional parameters that consist of climate zones and soil types alongside production cost and yield statistics and market value exports. The combination of economic indicator information with advanced forecasting tools will create valuable contributions to agricultural decision making for government bodies and crop selection practitioners and result in enhanced economic outcomes. The research applies machine learning technology to resolve regional crop management obstacles and create opportunities for innovative technological progress in Uzbekistan's agricultural industry.