Crop Planting Strategy based on Greedy Algorithm and Monte Carlo Simulation

Authors

  • Haoxu Miao

DOI:

https://doi.org/10.54097/zta23q63

Keywords:

Monte Carlo Simulation, Greedy Algorithm, Floating Parameters

Abstract

Crop cultivation is a complex process influenced by a multitude of environmental and market factors. To navigate these complexities and enhance profitability, this paper presents an innovative crop planting strategy. The strategy employs a combination of a greedy algorithm and Monte Carlo simulation techniques to optimize the allocation of crop cultivation. By analyzing historical planting and sales data, the proposed method aims to predict and maximize overall profitability. This approach not only considers immediate conditions but also incorporates a probabilistic assessment of various outcomes, providing a robust framework for decision-making in agricultural planning.

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References

[1] Huang Chengjian, Li Xiang, Liu Xiaokang, Pan Tingjie, Lei Ning, Luo Fang, Zhao Siyi The impact of different crop cultivation on soil and heavy metals in crops [J/OL] Crop Magazine: 1-10.

[2] Shi Gaojian, Wang Xinwei, Liu Qiang, Mu Li, He Jiayi Improved RRT~(*) algorithm for robotic arm path planning based on greedy strategy [J/OL] Manufacturing Technology and Machine Tools: 1-12.

[3] Xu Changming, Zhou Qilei, Wang Yichuan, Wang Dongnian, Jin Zhanggen, Wang Junwei Monte Carlo graph search for maintaining global game graph [J] Journal of Chongqing University of Technology (Natural Sciences), 2024, 38 (05): 130-136.

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Published

29-12-2024

Issue

Section

Articles

How to Cite

Miao, H. (2024). Crop Planting Strategy based on Greedy Algorithm and Monte Carlo Simulation. Frontiers in Computing and Intelligent Systems, 10(3), 54-58. https://doi.org/10.54097/zta23q63