Academic Journal of Agriculture & Life Sciences, 2025, 6(1); doi: 10.25236/AJALS.2025.060104.
Ruiyang Zhang1, Xinyao Wang2, Zhimei Li3
1School of Civil Engineering, Inner Mongolia University of Science & Technology, Baotou, 014010, China
2School of Economics and Management, Inner Mongolia University of Science & Technology, Baotou, 014010, China
3School of Digital and Intelligent Inoustry (School of Gyber Scienee and Technology), Inner Mongolia University of Science & Technology, Baotou, 014010, China
The application of digital agricultural technology aims to significantly enhance the efficiency and productivity of agricultural activities through advanced information technology and data analysis methods. However, globally, the growth rate of food production still lags behind the expansion rate of the population, leading to a serious issue: the limited nature of arable land resources. To address this challenge, the rational utilization and management of limited arable land resources have become one of the key strategies for improving the benefits of crop cultivation. In this paper, particle swarm optimization algorithm, Monte Carlo model and neural network model were used to optimize crop planting plan, increase crop planting quantity, planting area and annual planting frequency, reduce production cost, increase crop planting income, and maximize crop planting benefits. The results showed that adjusting crop planting plan had a great impact on crop planting income, and optimizing crop planting plan had a significant effect on improving crop planting income. At the same time, the intelligent optimization algorithm has a good performance in the optimization of crop planting scheme, and the optimization effect of the combined optimization algorithm is also worth looking forward to.
Particle Swarm Optimization (PSO), Monte Carlo Model, Crop Planting Scheme, Artificial Neural Network Architecture(ANN), Maximize revenue
Ruiyang Zhang, Xinyao Wang, Zhimei Li. The Study of Maximizing Profit in Crop Planting Plans Based on Optimization. Academic Journal of Agriculture & Life Sciences (2025), Vol. 6, Issue 1: 25-32. https://doi.org/10.25236/AJALS.2025.060104.
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