基于KPCA-WLSSVM的建筑能耗预测模型

为降低建筑能耗影响因素间复杂相关性对模型性能的影响,建立了一种基于KPCA-WLSSVM的建筑能耗预测模型。利用核主元分析(KPCA)对输入变量进行数据压缩,消除变量之间的相关性,简化模型结构;进一步采用加权最小二乘支持向量机(WLSSVM)方法建立建筑能耗预测模型,同时结合一种新型混沌粒子群-模拟退火混合优化(CPSO-SA)算法对模型参数进行优化,以提高模型的预测性能及泛化能力。通过将KPCA-WLSSVM模型方法应用于某办公建筑能耗的预测中,并与WLSSVM、LSSVM及RBFNN模型相比,实验结果表明,KPCA-WLSSVM模型方法能有效提高建筑能耗预测精度。     

The Monitoring Measurements and Country Rock Control of NATM in Tunnel of Express Road during Construction

In this paper the author' s study on the monitoring measurement technique of NATM,the regularity and conditions of the country rock deformation are analysed based on the site measurement data in the west section of Zhongliangshan tunnel. The regression analysis of measure data for different measure lines of vavious country rock is done by the use of self-compiled CRAP program. The stability criterion for various rockmass and optimum time for primary and permanent support are provided. The conclusion available could conduct the theoretical research of NATM deeply as well as tunnel design and construction.     

基于LS-SVM的小水电站年发电量智能预测模型

针对小水电站年发电量序列的特点,将最小二乘支持向量机(least squares support vector machine,LS-SVM)回归模型引入年发电量预测领域,并给出了相应的过程和算法。与常规基于人工神经网络(artificial neural net-works,ANN)的智能预测方法比较,该模型优点是明显的:①将神经网络迭代学习问题转化为直接求解多元线性方程;②整个训练过程中有且仅有一个全局极值点,确定了预测的稳定性。最后,一个实际的预测例子表明:该模型实现容易、预测准确,适用于小水电站预测。     

棉花膜下滴灌监控系统软件的设计

将工业自动化通用组态软件KingView和VB开发软件有机结合起来,设计棉花膜下滴灌智能决策与自动监控系统软件,并以数据库、模型库、知识库和方法库为技术核心,通过田间传感器进行数据实时采集、计算、分析与决策,由控制系统发送决策指令来控制灌溉设备开/闭,以提高灌溉的时效性。     

Water Pricing and Sustainability of Self-Governing Irrigation Schemes

The sustainability of self-governingirrigation schemes is currently underpressure in many countries as publicfinancial support is decreasing.Furthermore, growing global concernregarding water scarcity means thatefficient water use is essential.Theoretically the choice and implementationof a water-pricing system should play acentral role in achieving this objective,both by recovering water costs and byencouraging farmers to adopt more efficientbehaviour. In the Senegal River Delta newlyestablished water users associations (WUAs)have chosen low water charges, which areaffordable for the majority of farmers butwhich underestimate long-term maintenancecosts. Combined with the difficulty ofcollecting and managing farmers' fees, thischoice has drawn them into a vicious circleleading to scheme deterioration and poorwater service. New alternatives have beendiscussed with them using a simulation toolthat takes into account both the watercosts and the farmers' incomes. Comparedwith the present fixed water charge basedonly on cultivated land, a two-part optionbased both on equipped and irrigated areasensures the recovery of fixed expenses suchas maintenance, while encouraging farmersto intensify their farming systems byadopting double cropping. Neverthelesschoosing a relevant water charge does notensure by itself the sustainability of anirrigation scheme. Combined supportproviding WUAS and farmers with efficientadvice regarding management andorganisational skills should alsocontribute significantly to achieve thisprime objective.     

Monitoring forage production for farmers’ decision making

Objective management of grazing livestock production systems needs monitoring of forage production at the managerial unit level. Our objectives were to develop a system that routinely estimates forage above-ground net primary production (ANPP) at the spatial and temporal resolution required by farmers in the Pampas of Argentina, and to facilitate adoption of the system by end users as a managerial support tool. Our approach was based on the radiation use efficiency (RUE) logic, which proposes that ANPP is determined by the amount of photosynthetically active radiation absorbed by the canopy (APAR), and the efficiency with which that energy is transformed in above-ground dry matter (radiation use efficiency, RUE). APAR is the product of incoming photosynthetically active radiation (PAR) and the fraction absorbed by the canopy (fPAR). We estimated fPAR as a non-linear function of MODIS normalized difference vegetation index (NDVI). RUE was empirically estimated for the two principal forage resources of the region, yielding the following relations: ANPP = 0.6 × APAR + 12, (R² = 0.86; p < 0.001; n = 18) for the upland sown pastures, and ANPP = 0.27 × APAR + 26, (R² = 0.74; p < 0.001; n = 18) for the lowland naturalized pastures, with ANPP in g/m²/60 days and APAR in MJ/m²/60 days. The models were able to predict independent ANPP values with acceptable accuracy. Computational procedures were automated and run in a Relational Data Base Manager System that stored and managed all the information. The system is currently monitoring 212,794 ha in 83 farms and provides monthly ANPP values for the previous month and a history of the last 6 years. The data so generated show ANPP differences between the two major forage resources, considerable variability of a given month’s ANPP among years and paddocks, and contrasting among-farm differences in the efficiency of conversion of ANPP and forage supplements into beef production. The system was well accepted by end users who utilize it mainly for making near real time decisions according to last month ANPP, and explaining results of previous production cycles by incorporating ANPP as an explicative variable. However, there were differences among farmers in the degree of utilization, apparently related to the advisor’s attitude toward this new technology. Our results indicate that (1) forage production of large extensions can be monthly monitored at the paddock level by a small laboratory with capabilities in geographic information systems, and (2) advisors and farmers apply this information to their managerial decisions.     

Combining deliberative and computer-based methods for multi-objective land-use planning

This paper reports the outcomes of a deliberative workshop comparing land-use plans proposed by land-manager or domain experts with those derived using a computer-based decision support system (DSS). The DSS integrates four main components, a geographic information system, land-use systems simulation models, impact assessments and land-use planning tools. The land-use planning tools draw on the other components to generate and evaluate alternative patterns of land use and management. Since the land-use planning tools are based on multi-objective genetic algorithms (mGAs) it is possible to generate a range of alternative plans that define the structure of the trade-off between the objectives. The workshop tasked the delegates with specifying land-use plans that achieved the best compromise between two objectives known to be non-commensurable and conflicting. The nature of the best compromise was dependent on their individual perspectives. The delegates proposed allocations both as individuals and in researcher-facilitated sub-groups. The mGA allocations were then compared with those derived by delegates and were found to be broadly similar in performance. Differences in the range of allocations considered feasible were explained by the hard and soft constraints on allocations agreed between the delegates and articulated within the workshop process. The hypothesis that part of the difference in performance between the mGA and delegate allocations was due to the delegates blocking together fields with the same land use for convenience of management was proved. The analysis of the group allocations revealed that the decision-making process had failed to improve on the individual allocations. From these results it was concluded that there was a potential role for mGA based land-use planning tools in researching into, and deliberating on, the possible impacts of policy or other factors affecting land-use systems. It was further concluded that the tools should not be used in isolation since there was the need for stake-holder inputs to adequately define the range of feasible and practical land-use plans.     

基于PCA-GA-SVM的甘蔗收获机运行状态识别

由于甘蔗收获机在收获过程中智能化水平较低,依靠人工操作很容易对甘蔗收获机的运行状态产生误判,从而造成物流通道堵塞、能源浪费、收割效率低。针对这些问题,提出一种基于主成分分析(PCA)、遗传算法(GA)和支持向量机(SVM)状态识别模型。首先,通过实地采集甘蔗收获机刀盘轴、行走轴、切段轴和风机轴扭矩和行驶速度特征信息,然后通过PCA进行数据降维,最后利用GA优化参数C、γ,使用每个特性信息来训练SVM,对甘蔗收获机运行状态进行分类。结果表明:PCA-GA-SVM状态识别模型对甘蔗收获机运行状态的识别准确率为93.75%,建模时间为3.688 s,与SVM(81.25%,9.487 s)、PCA-SVM(87.5%,5.817 s)和GA-SVM(90%,8.969 s)进行对比,该模型具有最高准确识别率和最快建模速度,具有较大的应用价值。     

Mitigating nitrous oxide emissions from agricultural soils by precision management

Nitrous oxide (N₂O) emissions make up a significant part of agricultural greenhouse gas emissions. There is an urgent need to identify new approaches to the mitigation of these emissions with emerging technology. In this short review four approaches to precision managements of agricultural systems are described based on examples of work being undertaken in the UK and New Zealand. They offer the opportunity for N₂O mitigation without any reduction in productivity. These approaches depend upon new sensor technology, modeling and spatial information with which to make management decisions and interventions that can both improve agricultural productivity and environmental protection.     

公共财政支持"三农"发展的对策研究

中国自古以来都是以农业大国闻名世界,精耕细作、小农经济是传统中国经济的象征。所 以,中国政府也一直致力于农业的发展建设。目前,“三农”问题是中国共产党所要改善和提升的主要 对象。国内基层群众大部分都属于农民。由此可见,推动农业的发展是当前中国共产党势在必行的 任务。