Research on Crop Planting Strategy Optimization Based on Fuzzy C-Means Clustering and Generalized Additive Model

Jingjing Lin

doi:10.54097/42hak470

Authors

Jingjing Lin

DOI:

https://doi.org/10.54097/42hak470

Keywords:

Crop Planting Strategy Optimization, Linear Programming, Fuzzy C-Means Clustering, Generalized Additive Model.

Abstract

Against the backdrop of global climate change and resource scarcity, optimizing farmland planting strategies is crucial for improving agricultural production efficiency and achieving sustainable development. Current research primarily focuses on crop planting structures, but discussions on crop substitutability and legume complementarity remain insufficient. This study aims to explore crop planting strategies in a village in the North China region, particularly how to flexibly adjust planting structures under market fluctuations to maximize profits. The study employs fuzzy C-means clustering to analyze crop substitutability and incorporates legume complementarity, using a generalized additive model to predict sales volumes. The results show that considering substitutability and complementarity increases profits by approximately 1.08 times compared to pre-optimization levels, demonstrating that flexible planting strategies can effectively enhance profitability. Furthermore, the optimized planting plan improves farmland utilization rates. The findings provide valuable references for agricultural production, highlighting the potential of rational planting structures to enhance economic benefits.

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