Optimisation of Crop Planting Strategies Based on Dynamic Planning Models

In today's society, agricultural production faces many challenges, including population growth, resource scarcity, climate change and changes in market demand. In order to meet the growing demand for food, farmers need to optimise their cropping strategies to improve the efficiency of land and resource use for sustainable development. In this context, the optimisation of crop cultivation has gradually attracted extensive attention from academics and agricultural producers. Through the use of modern data analysis techniques, researchers can better understand the economic benefits of different crops and their interrelationships, and thus provide farmers with practical planting advice. In order to study to get the optimal strategy of crop planting in a certain countryside, this paper proposes a dynamic planning model to determine the optimal planting scheme of crops. In this paper, firstly, we take the profit as a clustering index, and use the K-means++ clustering algorithm to classify crops into three classes of high profit, medium profit and low profit. It is found that mushroom, vegetable and grain crops almost exactly correspond to these three profit classes, which provides effective theoretical support for the development of optimal planting strategies. Subsequently, for many problems in real life, this paper establishes a dynamic planning model, systematically solves a variety of practical constraints, and proposes the optimal planting scheme. Finally, this paper finds the optimal planting programme from 2024 to 2030 and the maximum profit to provide guidance for practical agricultural production activities.