Application Research on Corn Fertilization Optimization Using Random Forest Coupled with Cuckoo Search

With the advancement of the smart agriculture industry, the development of advanced fertilization technology has become crucial. However, current fertilizer distribution methods face issues such as low accuracy and prolonged periods. To address these issues, research has been conducted to enhance the application of forest enrichment techniques, cuckoo search algorithms, and semi-fertilization models for rice. Initially, it is important to set the amount of fertilizer in advance. Subsequently, the amount of fertilizer should be adjusted as needed, followed by improvements in the utilization of forestry calculations and crop yield simulations. By integrating the Cuckoo Search algorithm, the optimal amount of fertilizer can be determined. This method establishes soil characteristics and aims to maximize fertilizer application, thereby achieving high efficiency and precise distribution. Based on this model, an intelligent fertilizer system has been developed, enabling effective management and distribution of fertilizers.