人工湿地优化设计方法研究

在总结国内外人工湿地传统设计方法的基础上,引入了Monod反应动力学模型和离散型水流流动模型.通过对人工湿地系统特别是对垂直复合流人工湿地系统重要水力学问题的分析研究,改进传统的根据一级反应动力学模型的设计方法,提出了复合垂直流人工湿地的优化设计方法.笔者提出的新的人工湿地结构参数推算方法,在设计的准确性和经济性等方面较传统设计方法有了较大的提高,将对人工湿地工程的构建有一定的指导意义.     

The rehabilitation of an irrigation system along the Yellow River

The People's Victory Irrigation System which diverts water from the Yellow River of China covers a total irrigable area of 59 000 ha. The system encountered some serious problems in the first decade of its operation — salinity and waterlogging of irrigated land, siltation of irrigation and drainage channels, as well as a low efficiency of water use. This paper describes a series of structural and functional measures which have been adopted in the past 24 years for the rehabilitation of the system, including: improvement of the existing drainage system and construction of new drainage system on agricultural land, conjunctive use of surface and groundwater supplies, a comprehensive programme to reduce the levels of siltation as well as the implementation of improved water management practices. A model for the optimal operation of the system by using system analysis theory as an aid in reducing the operation and maintenance (O & M) costs has been developed in recent years. The results are that the soil salinity has been controlled and the agricultural production has increased whilst the efficiency of water use has improved and the siltation levels reduced. Experience gained on this system has been successfully used in developing and managing other irrigation projects along the lower reaches of the Yellow River. The proposed procedure of solving the said optimal model has also embodied some benefits from reducing O & M costs in operation.     

自压式树状管网的两级优化设计模型与神经优化设计

建立了自压式树状管网两级优化设计模型，并用人工神经网络法实现树状管网非线性规划模型的快速求解。采用的人工神经网络技术的两级优化设计模型在适用范围、求解速度和获得最优解能力上，均优于单一的非线性规划模型和线性规划模型，是实现树状管网全局优化设计的一条新途径。     

基于损失模型的电磁制动器稳健优化设计

介绍了基于损失模型的稳健设计的两个基本工具:信噪比和正交试验设计,讨论了设计的基本思想和步骤。建立合理的数学模型,对电磁制动器结构参数进行了稳健优化设计。并将结果与传统优化结果进行了比较、分析和讨论,结果表明,稳健设计后的电磁制动器的性能得到了较大的改善和提高。     

冬小麦节水高效优化灌溉制度模型应用研究

根据霍泉灌区田间试验资料,考虑水分亏缺的后效性,以冠层叶面积指数修正后的作物-水模型作为目标函数,建立二雏动态规划模型,计算冬小麦节水高效优化灌溉制度。结果显示,该模型充分反映了灌水时间、灌水定额和灌溉水量产生的冬小麦的产量效应,所建模型和参数确定较合理,在实践中更有实用性。     

陈垓引黄灌区渠系优化配水研究

该文以系统工程的原理方法,结合山东省陈垓引黄灌区北二干渠系统实际情况,分别以灌溉净效益最大和轮灌时间最短为目标,建立了作物最优种植面积和渠系优化配水模型,应用计算机求解,取得了满意的作物优化布局和优化配水成果。实践证明,本项成果在节水、灌溉增产、提高灌区科学管理水平等方面都有着十分重要的作用。     

竞争型指派问题的匈牙利方法

标准的指派问题以人员指派为例大都满足以下三个前提假设:人数等于任务数;每个人必须且只需完成一项任务;每项任务必须且只需一人去完成。但在实际应用中,大多的指派问题并不具备第一个假设,而第二个假设又显然不符合当今引进竞争机制后的企业、部门及社会的要求。针对以上弊端,张琳先生曾提出了竞争型指派问题,摒弃了前两个假设,从根本上拓广了标准指派问题的应用范畴。文章将重点提出竞争型指派问题的详细的算法—竞争型指派问题的匈牙利方法。     

玉米苗枯病抗性鉴定方法的改进

采用玉米种子培养液对串珠镰刀菌分生孢子萌发抑制率和串珠镰刀菌毒素对玉米胚根、胚芽生长抑制率作为玉米苗枯病抗病鉴定指标,并与21个杂交玉米种苗枯病田间发病率进行相关分析来验证其准确性.结果表明,串珠镰刀菌毒素对玉米胚根、胚芽生长抑制率与玉米苗枯病田间发病率相关性较高,相关系数分别为0.925、0.919.该两种方法结果准确,可以作为玉米苗枯病抗性鉴定指标.     

Deep neural network algorithm for estimating maize biomass based on simulated Sentinel 2A vegetation indices and leaf area index

Accurate estimation of biomass is necessary for evaluating crop growth and predicting crop yield.Biomass is also a key trait in increasing grain yield by crop breeding.The aims of this study were(i)to identify the best vegetation indices for estimating maize biomass,(ii)to investigate the relationship between biomass and leaf area index(LAI)at several growth stages,and(iii)to evaluate a biomass model using measured vegetation indices or simulated vegetation indices of Sentinel 2A and LAI using a deep neural network(DNN)algorithm.The results showed that biomass was associated with all vegetation indices.The three-band water index(TBWI)was the best vegetation index for estimating biomass and the corresponding R2,RMSE,and RRMSE were 0.76,2.84 t ha−1,and 38.22%respectively.LAI was highly correlated with biomass(R2=0.89,RMSE=2.27 t ha−1,and RRMSE=30.55%).Estimated biomass based on 15 hyperspectral vegetation indices was in a high agreement with measured biomass using the DNN algorithm(R2=0.83,RMSE=1.96 t ha−1,and RRMSE=26.43%).Biomass estimation accuracy was further increased when LAI was combined with the 15 vegetation indices(R2=0.91,RMSE=1.49 t ha−1,and RRMSE=20.05%).Relationships between the hyperspectral vegetation indices and biomass differed from relationships between simulated Sentinel 2A vegetation indices and biomass.Biomass estimation from the hyperspectral vegetation indices was more accurate than that from the simulated Sentinel 2A vegetation indices(R2=0.87,RMSE=1.84 t ha−1,and RRMSE=24.76%).The DNN algorithm was effective in improving the estimation accuracy of biomass.It provides a guideline for estimating biomass of maize using remote sensing technology and the DNN algorithm in this region.     

基于卷积神经网络的小麦产量预估方法

小麦产量是评估农业生产力的重要指标之一,针对小麦产量人工预估困难,提出将卷积神经网络运用于小麦产量预估,为农业生产力的预估提供参考,指导农业生产管理决策。利用无人机分别在河南省新乡、漯河两地进行图片采集,并以之构建麦穗数据集,分为正样本(麦穗)和负样本(叶子和背景)。针对小麦常规的生理形态和生长环境,设计卷积神经网络识别模型,以图像金字塔构建多尺度滑动窗口,以非极大值抑制(NMS)去除重叠率较高的目标框,实现对单位面积内麦穗的计数,并利用随机采样的方式对大田麦穗进行单位面积图像采样,以采样图像中麦穗数量的平均值作为产量预估基准,进一步实现麦穗产量预估。随机抽取100幅不同小麦图片进行测试,与人工计数结果进行对比,准确率达到97.30%,漏检率为0.34%,误检率为2.36%,误差率为2.70%。试验结果表明,此方法能够克服环境中的多种噪声干扰,能够在不同光照条件下对麦穗进行计数和产量预估。