Statistical Analysis and Modeling Research Based on Crop Planting Strategies in Rural Areas

Abstract

According to specific rural conditions, rational planning of organic farming, selection of crops and fine management of planting play a key role in promoting the long-term stable growth of local economy. This paper focuses on the development of agricultural planting in North China, and establishes a planting structure optimization model based on global search for the planting problems of agriculture of different plot types, combined with price reduction, uncertainties and potential risks. By considering the changes of economic parameters such as expected sales volume, planting cost, yield per mu and sales price of crops, this paper constructs a target planning model to maximize economic returns, and uses a global search optimization algorithm based on dynamic programming and greedy algorithm to solve the problem. The results show that the economic benefits of crop planting can be improved by rationally adjusting the planting structure, while avoiding food waste and protecting food security. In addition, this paper also considers the fluctuations of crop yield, cost and selling price in the future, as well as the sales growth trend of different crops, and establishes an uncertainties-based crop planting structure optimization model to adapt to market fluctuations and climate instability, and ensure considerable economic benefits in a volatile environment.