| 引用本文: | 李彦彬,马嘉彤,李道西,等.改进粒子群算法在农业种植结构优化中的应用[J].灌溉排水学报,0,():-. |
| LI Yanbin,MA Jiatong,LI Daoxi,et al.改进粒子群算法在农业种植结构优化中的应用[J].灌溉排水学报,0,():-. |
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| 摘要: |
| 【目的】为促进地区农业水资源高效利用,在保证粮食安全的基础上,降低灌溉需水量,提高效益。【方法】以安阳市为例,综合选取经济、社会、生态和水资源效益最大为目标,引入惯性权重递减和粒子变异策略,建立基于改进粒子群算法的多目标农业种植结构优化模型。【结果】通过对现状水平年2018年、规划水平年2025年(近期)、2035年(远期)的种植结构调整,在结合现状缺水程度下,压减耗水量大的小麦、玉米等粮食作物种植比例,增加油料、蔬菜及食用菌等经济作物种植比例,包含经济、社会、生态、水资源目标的综合效益得到了提升；同时,在满足农作物全生育期需水量的情况下缺水率缩减,在一定程度上缓解了农业水资源供需矛盾。【结论】该研究旨在对地区粮经作物的种植结构比例进行平衡优化,节省农田灌溉用水量,以期对农业水资源进一步优化管理提供理论依据和数据支撑。 |
| 关键词: 种植结构优化;水资源优化;多目标规划;农业节水;改进粒子群算法 |
| DOI： |
| 分类号:S5-3；S27 |
| 基金项目:国家自然科学基金项目,国家自然科学基金项目（面上项目，重点项目，重大项目） |
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| Application of Improved PSO Algorithm in Agricultural Planting Structure Optimization |
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LI Yanbin, MA Jiatong, LI Daoxi, WANG Fei
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North China University of Water Resources and Electric Power
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| Abstract: |
| 【Objective】 In order to improve the efficient use of regional agricultural water resources, it is necessary to reduce the irrigation water demand. 【Method】 Taking Anyang City as an example, the objective was to select the greatest economic, social, ecological, and water resources benefits in a comprehensive manner. The inertia weight decay strategy and particle mutation strategy were introduced to establish a multi-objective agricultural planting structure optimization model based on an improved particle swarm optimization algorithm.【Result】By adjusting the planting structure in the base year and plan years, the proportion of grain crops such as wheat and corn that consume a large amount of water was reduced, while the proportion of cash crops such as oil-bearing crops, vegetables, and edible fungus was increased, so that the comprehensive benefits were improved. The supply-demand contradiction of agricultural water resources was alleviated to a certain extent while meeting the water demand of crops during the whole growth period. 【Conclusion】The study aims to optimize the balance of regional planting structure ratio and ensure food security, which is used to provide the theoretical basis and data support for further optimization of agricultural water resources management. |
| Key words: planting structure optimization; water resources optimization; multi-objective planning; agricultural water saving;improved particle swarm optimization |
