基于遗传算法-生成对抗神经网络模型的宁夏自流灌区水资源优化调度研究

doi:10.14088/j.cnki.issn0439-8114.2021.15.036

湖北农业科学 ›› 2021, Vol. 60 ›› Issue (15): 174-180.doi: 10.14088/j.cnki.issn0439-8114.2021.15.036

基于遗传算法-生成对抗神经网络模型的宁夏自流灌区水资源优化调度研究

董陈超

河海大学商学院,江苏常州 213022

收稿日期:2020-11-26 出版日期:2021-08-10 发布日期:2021-08-18
作者简介:董陈超（1999-）,男,江苏扬州人,在读本科生,专业方向为数据挖掘、情报分析,（电话）19951081007（电子信箱）2605485335@qq.com。
基金资助:
国家社会科学基金项目（17BTQ055）; 河海大学中央高校基本科研业务费资助项目（2018B04614）

Optimal dispatching of water resources in artesian irrigation district of Ningxia based on genetic algorithm-generative adversarial neural network model

DONG Chen-chao

Business School, Hohai University,Changzhou 213022,Jiangsu,China

Received:2020-11-26 Online:2021-08-10 Published:2021-08-18

摘要/Abstract

摘要： 针对宁夏自流灌区灌溉用水存在农作物耗水量大、用水集中、灌溉效率低等现象,面向宁夏区域用水实际,围绕渠道进水闸和出水口,以满足农田基本灌溉用水为前提,以灌溉效率最大化为目标,采用机器学习方法,构建遗传算法-生成对抗神经网络的宁夏自流灌区水资源优化调度模型,并在宁夏秦汉渠管理处农场渠所管辖的30余公里渠道及其灌区进行验证和应用。结果表明,模型在学习传统调度方案的基础上深度挖掘各取水口用水规律,实现高效的取水口联合调度,月节约灌溉用水315 109~1 050 362 m³,显著提高了宁夏水资源利用效率。

关键词: 灌溉水资源, 优化调度, 遗传算法, 生成对抗神经网络, 机器学习

Abstract: In view of the phenomena of large crop water consumption, concentrated water use, and low irrigation efficiency in Ningxia artesian irrigation area. According to the actual water use in Ningxia, focusing on the water inlet and outlet of the channel, the premise is to meet the basic irrigation water of farmland, and the goal is to maximize irrigation efficiency. Using machine learning methods to build genetic algorithm-generative adversarial neural network model in Ningxia artesian irrigation districts, and verify and apply them in more than 30 kilometers of channels and irrigation areas of the Qinhan Canal Management Office in Ningxia. The results show that the model deeply excavates the water usage rules of each water intake on the basis of learning traditional scheduling schemes, establishes efficient water intake joint scheduling irrigation methods, saves 315 109~1 050 362 m³ of irrigation water per month, and significantly improves the efficiency of water resource utilization in Ningxia.

Key words: irrigation water resources, optimal schedule, genetic algorithm, generative adversarial neural network, machine learning

中图分类号:

TV213.9

董陈超. 基于遗传算法-生成对抗神经网络模型的宁夏自流灌区水资源优化调度研究[J]. 湖北农业科学, 2021, 60(15): 174-180.

DONG Chen-chao. Optimal dispatching of water resources in artesian irrigation district of Ningxia based on genetic algorithm-generative adversarial neural network model[J]. HUBEI AGRICULTURAL SCIENCES, 2021, 60(15): 174-180.

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基于遗传算法-生成对抗神经网络模型的宁夏自流灌区水资源优化调度研究

Optimal dispatching of water resources in artesian irrigation district of Ningxia based on genetic algorithm-generative adversarial neural network model

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