陕西关中灌区基层管理体制改革监测评价网络体系

系统介绍陕西省关中灌区基层管理体制改革监测评价网络体系的组成、运作程序，实施中存在的主要问题及改进意见，并总结了开展监测评价工作的经验。建立关中灌区管理体制改革监测评价网络系统，对指导与促进九大灌区基层管理体制改革工作的平稳而深入发展起到了积极的作用，而且有关建立监测评价网络体系的经验与做法，对中国各灌区开展此项工作均有一定的指导意义与参考价值。     

大田农业节水物联网技术应用现状与发展趋势

物联网技术与农业领域应用的结合是推动传统农业向现代农业转型升级的重要驱动力,农业节水是中国农业发展长期关注的重点。以物联网技术感知层、传输层、应用层架构为主线,针对大田主要粮食作物水分需求,总结物联网技术在大田农业节水关键环节中的应用发展现状以及存在的局限性,并在大数据、云计算等现代信息技术发展基础上,结合新时期互联网+战略,对物联网技术快速发展态势下农业节水技术、服务、模式的未来发展趋势进行探讨,提出技术向服务转变、决策向预测转变、微观向宏观转变的发展思路。     

基于RAdam卷积神经网络的水稻生育期图像识别

为了解决现阶段水稻发育期信息的获取主要依靠人工观测的效率低、主观性强等问题,该研究提出一种基于Rectified Adam(RAdam)优化器的ResNet50卷积神经网络图像识别方法,开展水稻关键生育期的自动识别。连续2a对12块试验田的水稻物候特征进行持续自动拍摄,对采集的水稻图像进行预处理,得到水稻各发育期分类图像数据集;采用ExG因子和大津法(Otsu)算法相结合的方法对水稻图像分割,减小稻田背景干扰;对比分析了VGG16、VGG19、ResNet50和Inception v3四种模型下水稻生育期图像分级识别的性能,选取性能较优网络模型并进行了网络参数调优;对比试验了不同优化器下模型准确率和损失值的变化,选取了RAdam优化器。结果表明,采取基于RAdam优化器卷积神经网络构建的模型,在真实场景下分类识别准确率达到97.33%,网络稳定性高、收敛速度快,为水稻生育期自动化观测提供了有效方法。     

The application of rough sets-neural network theory to mine ventilation system evaluation

To solve the instability problem of established sample in the neural network evaluation method for mine ventilation system, a comprehensive evaluation of the ventilation system is carried out based on rough sets and BP neural networks. Taking the ventilation system of a mine as an example, the classification quality of raw data samples are tested by using rough set data analysis system. Then, based on artificial neural network theory, a rough sets-neural network evaluation model of a mine ventilation system is established and a new rough sets-neural network evaluation method of mine ventilation system is formed. The results show that, after the model validation of data and application, its theoretical evaluation results are in line with the actual situation, and the network total error is less than 0.004. It shows that the comprehensive evaluation method based on rough sets-neural networks has a good effect in evaluating mine ventilation system in practical application.     

Spatially targeting the distribution of agricultural input stockists in Malawi

Developing the rural agricultural input markets in sub-Saharan Africa can improve the current low productivity of smallholder farmers. Malawi has seen significant efforts in addressing the availability of agricultural inputs at village level in the last few years; for example, the improvement of rural agro-dealer networks. Nevertheless inputs are still difficult to obtain for many remote smallholder farmers. Spatial analysis can help in the expansion of input stockists, especially agro-dealer networks, by assessing the coverage of existing input outlets and deriving optimum locations for village-level input stockists.We address three research questions. First, what is the locational efficiency of the current village-level stockists of inputs (Citizens Network for Foreign Affairs – Rural Agricultural Market Development Trust trained network of agro dealers and public sector)? Secondly, how many village-level stockists of markets are needed to reach 60% of the population in the central region of Malawi within one hour? Finally we address the potential spatial components of the sustainability of input stockists relating to the potential demand from smallholder farmers and the access to bulk supplies. The problem of finding the optimum location for village-level stockists of markets is addressed in two stages, using spatial analysis in conjunction with location–allocation models. First, the locational efficiency of the existing network of stockists of inputs is determined, followed by the establishment of a set of optimal sites for village-level stockists of inputs. A final step explores the viability of stockists and calculates the population surrounding the stockists taking into account competition from other sources of inputs and the accessibility of the selected stockists to potential wholesalers who are bulk distributors of farm inputs.Our results show that locational efficiency can be assessed in terms of the differential access of households to resources and transport. Often, these differences are not considered in covering problems and can have a large effect on the physical access to inputs. The results can be used to define which areas are inherently difficult to serve with agricultural inputs and could inform efforts to provide incentives to remote areas. Further implications for input policies in Malawi are that improvements in road infrastructure might not directly benefit the poorest farmers (if they are walking) but could serve to reduce the wholesale prices and therefore the retail price. In addition, the improvement in roads might increase the number of potential customers of any particular stockist, with economies of scale allowing the reduction of prices while ensuring a satisfactory profit margin for the stockist. The results of our models imply that Citizens Network for Foreign Affairs may need to train stockists over a wider area to increase the access to inputs of those smallholder farmers with least resources.     

以人文关怀推动校园网文明建设与发展

人文关怀在校园网建设与管理中意义重大, 它不仅是推进素质教育、提高教学水平的需要, 也是学校跨越式发展的需要, 是校园文明建设制度的体现。具体而言, 人文关怀可以促进文明办网、健康上网,也可以提升网络功能, 真正把校园网文明建设落到实处。     

稻飞虱预报方法研究

对四川省稻飞虱常发区的灯下，田间稻飞虱资料及４－６月各旬的温度，降水量，相对湿度等因子，用神经网络的Ｂａｃｋ Ｐｒｏｐａｇａｔｉｏｎ算法进行分析，并对发生程度试报，效果较好。     

证券市场灰色神经网络组合预测模型应用研究

提出将3种灰色模型(残差GM(1,1),无偏GM(1,1)和pGM(1,1))与神经网络模型进行有机组合,建立一种新的灰色神经网络组合预测模型,并以中国股票市场上证指数为例进行模拟预测.实证表明:组合预测模型的模拟预测精度较原有方法更为精确,可作为股市预测的有效工具.     

一种改进的天然气管网流动方程表示方法

针对应用关联矩阵法在描述天然气管网流动方程时未考虑压气站的自耗气,在准确描述该部分气量的模型中易产生偏差的问题,通过增加自耗气源向量的方法对此进行了改进,可以完整地描述这部分天然气,准确地对管网的结构和管网的流动方程进行描述。     

基于神经网络的一类非线性关联大系统鲁棒滑模分散控制

针对一类具有未知界扰动和子系统部分已知的非线性大系统,结合神经网络逼近方法、滑模控制研究了一种新的分散鲁棒自适应控制方法。所设计的分散控制器分为两部分,一是等效控制器,二是滑模控制器。滑模控制器用来减小系统的跟踪误差,起鲁棒控制作用。文中用神经网络逼近非线性未知函数,将网络权值误差引入到网络权值的自适应律中用以改善系统的动态性能。仿真算例证明了所设计的鲁棒分散控制器是有效的。