%0 Journal Article %T 基于MATLAB的农作物种植策略优化研究
Optimization of Crop Planting Strategy Based on MATLAB %A 王乔仪 %A 蔡昌友 %J Modeling and Simulation %P 1052-1059 %@ 2324-870X %D 2025 %I Hans Publishing %R 10.12677/mos.2025.141096 %X 本研究聚焦于现代农业生产中农作物种植策略的优化问题，目的在于通过科学配置作物与土地资源，结合MATLAB工具构建优化模型，以实现种植收益的最大化。收集的作物数据，运用线性回归模型对关键变量进行了相关性分析，针对农作物市场状况不变的前提，构建了基于静态销售价格的种植优化模型，考虑了超出预期销售量部分作物滞销或降价销售的两种策略，并运用优化算法为每块土地分配最优种植方案。研究发现，降价销售策略能够有效提升整体收益。同时，研究还构建了基于不确定性的多阶段优化模型，以适应市场和气候的不确定性，动态优化种植方案。本研究提出的模型能够为不同土地在未来数年内提供最优种植方案，同时考虑了市场变化、作物轮作等多重现实约束。为农业种植策略的优化提供理论支持和实践指导。
This study focuses on the optimization of crop planting strategies in modern agricultural production. The purpose is to construct an optimization model by scientifically allocating crop and land resources and combining MATLAB tools to maximize the benefits of planting. Based on the collected crop data, the linear regression model was used to analyze the correlation of key variables. Aiming at the premise of unchanged crop market conditions, a planting optimization model based on static sales price was constructed. Two strategies of unsalable or reduced-price sales of some crops beyond the expected sales volume were considered, and the optimization algorithm was used to allocate the optimal planting plan for each land. The study found that the price reduction sales strategy can effectively improve the overall revenue. At the same time, the study also constructed a multi-stage optimization model based on uncertainty to adapt to the uncertainty of market and climate and dynamically optimize the planting plan. The model proposed in this study can provide optimal planting schemes for different land in the next few years, taking into account multiple realistic constraints such as market changes and crop rotation. It provides theoretical support and practical guidance for the optimization of agricultural planting strategies. %K 多元线性回归， %K 粒子群算法， %K 农作物种植优化模型， %K 多阶段优化
Multiple Linear Regression %K Particle Swarm Optimization %K Optimization Model for Crop Planting %K Multi-Stage Optimization %U http://www.hanspub.org/journal/PaperInformation.aspx?PaperID=105983