Research on Crop Planting Strategies Based on K-means Clustering and Optimisation Models

This paper investigates the strategy of optimisation model for rural crop cultivation with a view to develop the best cultivation plan for the next seven years. An optimisation model with the objective of profit maximisation has been developed by taking into account the expected sales volume, acreage, cost of cultivation and selling price of various crops and their uncertainty risks. The model incorporates the complex constraints of the actual production process and takes into account multiple uncertainties such as changes in market dynamics and fluctuations in climatic conditions by analysing four scenarios, namely optimal, suboptimal, intermediate and stochastic, which makes the model much more practical. In addition, this paper applies the K-means clustering method to explore the substitution and complementary relationship between different crops, which makes the model more in line with the actual market law. The results show that a reasonable planting strategy can not only enhance the economic benefits of crops, but also promote the efficient use of resources and sustainable development of the environment. The optimisation model proposed in this paper provides scientific guidance for agricultural decision makers and provides a reference for the production strategies of other products. Future research can be further extended to other regions and crop types to improve the overall strategic layout of agricultural production and promote the high-quality development of agriculture.

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Publication Details

Journal
Highlights in Science Engineering and Technology
Published
2024-12-11
DOI
https://doi.org/10.54097/5411by63
Primary Topic
Wireless Sensor Networks and IoT
Type
article
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article

Research on Crop Planting Strategies Based on K-means Clustering and Optimisation Models

Tianyu Yuan
Highlights in Science Engineering and Technology
Wireless Sensor Networks and IoT
article

Research on Crop Planting Strategies Based on K-means Clustering and Optimisation Models

Tianyu Yuan
article en

Abstract

This paper investigates the strategy of optimisation model for rural crop cultivation with a view to develop the best cultivation plan for the next seven years. An optimisation model with the objective of profit maximisation has been developed by taking into account the expected sales volume, acreage, cost of cultivation and selling price of various crops and their uncertainty risks. The model incorporates the complex constraints of the actual production process and takes into account multiple uncertainties such as changes in market dynamics and fluctuations in climatic conditions by analysing four scenarios, namely optimal, suboptimal, intermediate and stochastic, which makes the model much more practical. In addition, this paper applies the K-means clustering method to explore the substitution and complementary relationship between different crops, which makes the model more in line with the actual market law. The results show that a reasonable planting strategy can not only enhance the economic benefits of crops, but also promote the efficient use of resources and sustainable development of the environment. The optimisation model proposed in this paper provides scientific guidance for agricultural decision makers and provides a reference for the production strategies of other products. Future research can be further extended to other regions and crop types to improve the overall strategic layout of agricultural production and promote the high-quality development of agriculture.

Highlights in Science Engineering and TechnologyVol. 119
China University of Petroleum, Beijing (CN), Karamay Central Hospital (CN)
Zero hunger
Openalex Percentile: Top 73%
Wireless Sensor Networks and IoT
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Research on Crop Planting Strategies Based on K-means Clustering and Optimisation Models — Tianyu Yuan · Highlights in Science Engineering and Technology (2024) | TGRS Research Map | TGRS