Research on Crop Planting Strategies Based on K-means Cluster Analysis and Linear Programming
The purpose of this paper is to explore the application of K-Means cluster analysis and linear programming model in agricultural production. Firstly, the linear programming model is used to formulate the planting strategy in the region, taking the actual situation in North China as an example. Secondly, on the basis of the optimization of the linear programming model, a preliminary crop planting strategy is given. A robust optimization model is introduced to construct the uncertainty set and incorporate it into the objective function to obtain the optimal planting strategy in the worst case. Finally, the objective function was improved by K-Means cluster analysis model and the model was refined by integrating the substitutability and complementarity among crops. The model aims to improve the economic efficiency of local farmers and provide a reference for agricultural planning in other regions.
Authors
- Zhaohua Yin (ORCID: https://orcid.org/0000-0002-4750-1780)
- Wenke Yuan (ORCID: https://orcid.org/0000-0003-3702-9619)
- Lei Xia (ORCID: https://orcid.org/0000-0003-0915-4527)
Institutions
- Guizhou University (CN)
Publication Details
- Published
- 2024-12-29
- DOI
- https://doi.org/10.1109/iceace63551.2024.10898646
- Citations
- 1
- Primary Topic
- Remote Sensing and Land Use
- Type
- article
- Field-Weighted Citation Impact
- 0.38