...
首页> 外文期刊>Neural computing & applications >Cuckoo optimization algorithm in optimal water allocation and crop planning under various weather conditions (case study: Qazvin plain, Iran)
【24h】

Cuckoo optimization algorithm in optimal water allocation and crop planning under various weather conditions (case study: Qazvin plain, Iran)

机译:杜鹃优化算法在各种天气条件下最优水分配和作物规划(案例研究:伊朗QAZVIN PLAN)

获取原文
获取原文并翻译 | 示例
   

获取外文期刊封面封底 >>

       

摘要

As inferred from its biological nature, agriculture is a key consumer of water resources in many countries. Hence, today, water management plays an important role in the use of water resources of these countries. The present study aimed to optimize cultivation area, to manage irrigation water, and to optimize total income gained from the cultivation area of special crops in Qazvin plain (the central plateau of Iran) under various weather conditions using cuckoo optimization algorithm (COA). Under the same objective function, the performance of the COA was accessed through comparison with the genetic algorithm (GA). The results of two models showed that because of its high water requirement and low yield, the cultivation area of sugar beet in every four different condition reduced (by over 80%); that is, it is not wise to plant it in all different weather conditions of the study area. Comparison of the model results indicates that the COA can provide better and more reliable optimal results in relative yield of crops, higher farm income. So, in comparison with GA, less water is allocated. Following the new cropping pattern delivered by COA model, the water volume stored in the dam reservoir at the end of the operation under wet, normal, dry, and hot-dry conditions rose, respectively, by 264,745.3, 2,865,387, 275,789, and 655,918m(3). Meanwhile, the farmers' profit increased, respectively, by 6.2, 2.6, 1.27, and 1.48% compared to the previous optimization occurred at the end of the operation. To conclude, COA is quite promising in a cultivation area of crops optimization problem in terms of its simple structure, excellent search efficiency, and strong robustness.
机译:从其生物学推断出来,农业是许多国家水资源的关键消费者。因此,今天,水管理在使用这些国家的水资源方面发挥着重要作用。本研究旨在优化栽培区,管理灌溉水,并在使用杜鹃优化算法(COA)的各种天气条件下,优化Qazvin Plane(伊朗中央高原)的特殊作物栽培区中所获得的总收入。在相同的客观函数下,通过与遗传算法(GA)进行比较访问COA的性能。两种模型的结果表明,由于其高水需求和低产量,每四种不同条件的甜菜培养面积减少(超过80%);也就是说,在研究区域的所有不同天气条件下植入它并不明智。模型结果的比较表明,COA可以提供庄稼相对产量的更好且更可靠的最佳结果,更高的农业收入。因此,与GA比较,分配了较少的水。遵循COA模型提供的新裁剪模式,分别在湿,正常,干燥和热干燥条件下的运作结束时储存在坝储存中的水量,分别升至264,745.3,2,865,387,275,789和655,918米(3)。与此同时,与先前的优化相比,农民利润分别增加6.2,2.6,1.27和1.48%。为了得出结论,根据其简单结构,优秀的搜索效率和强大的鲁棒性,COA在作物优化问题的培养面积中非常有前途。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号