基于优化的四心法画椭圆误差分析

用几何作图方法画已知长短轴的椭圆，有同心圆法和四心法两种方法。其中．同心圆法是通过准确求得椭圆上的若干点，然后用光滑的曲线徒手连接这些点而得到。点数求得越多．所得的椭圆就越准确．但由于其作图繁琐且得到的椭圆图线不圆滑而使其应用受到限制，而四心法由于其作图简单且得到的椭圆图线光滑而倍受青睐。为此，介绍了四心法近似画椭圆的作图方法，定性分析该方法作图的误差。并建立误差分析的数学模型，采用优化的方法进行定量分析。     

农业机械系统配备量优化研究

农业机械系统选型配套是研究机械化的重要基础性工作,同时也是确保优质和高效完成各项作业的重要条件。为此,对目前农业机械配备方法进行了研究与分析,提出采用流水作业下的农业机械线性规划配备模型来进行配备量研究,对农业机械化取得良好经济效益有很好的推进作用。     

带优先加工约束2×n型异序排序的简便解法

为解决异序排序问题,提出了新的表上作业法。该方法不仅可以解决2×n型异序排序问题,还可以有效地解决带优先加工约束2×n型异序排序问题。该方法简便易行,便于掌握,可获得比较满意的近似最优加工顺序。     

改性菠萝皮渣对Cu2+的吸附研究

采用五因子二次回归正交旋转组合设计的方法对影响改性菠萝皮渣吸附Cu2+的因子进行优化,得出在浓度60 mg/L、加入量1.2g、pH=5、时间2h、温度40℃时,改性菠萝皮渣有最大吸附率YMax=91.8%。吸附等温线研究表明吸附可能以单分子层吸附占优势。吸附速率模型研究表明二级动力学模型可以更好地描述吸附的动力学行为。活性炭对比试验表明改性菠萝皮渣对铜离子的吸附在低浓度时优于活性炭。扫描电镜下改性菠萝皮渣表面显示粗糙和多褶皱。改性菠萝皮渣对铜离子的吸附是物理和化学吸附相结合的吸附过程。     

Saccharomyces cerevisiae B9发酵生产S-腺苷甲硫氨酸的优化研究

以高产S-腺苷甲硫氨酸的菌株Saccharomyces cerevisiaeB9对培养基和发酵条件进行了优化研究。通过单因素水平测试和正交水平测试,确定了发酵培养基的最佳配方组合为:蔗糖8%、NH4Cl 0.5%、NH4H2PO40.2%、酵母提取物1.2%、MgSO4.7H2O 0.01%、KH2PO40.6%、L-甲硫氨酸1.2%,与原始发酵培养基相比,S-腺苷甲硫氨酸从1.16 g/L提高到3.35 g/L,菌体干重从16.18 g/L提高到18.25 g/L。在此基础上,对发酵条件进行优化,结果发现:初始pH5,培养温度30℃,摇床转速180 r/min为最佳培养条件。此时,菌体干重达19.86 g/L,S-腺苷甲硫氨酸产率达4.2 g/L。     

Towards the sustainable intensification of agriculture—a systems approach to policy formulation

The sustainable intensification of agriculture involves providing sufficient food and other ecosystem services without going beyond the limits of the earth’s system. Here a project management approach is suggested to help guide agricultural policy to deliver these objectives. The first step is to agree measurable outcomes, integrating formal policy goals with the often much less formal and much more diverse goals of individual farmers. The second step is to assess current performance. Ideally, this will involve the use of farm-scale metrics that can feed into process models that address social and environmental domains as well as production issues that can be benchmarked and upscaled to landscape and country. Some policy goals can be delivered by supporting ad hoc interventions, while others require the redesign of the farming system. A pipeline of research, knowledge and capacity building is needed to ensure the continuous increase in farm performance. System models can help prioritise policy interventions. Formal optimization of land use is only appropriate if the policy goals are clear, and the constraints understood. In practice, the best approach may depend on the scale of action that is required, and on the amount of resource and infrastructure available to generate, implement and manage policy.     

基于粒子群算法优化BP神经网络的土壤含水量短期预测模型

为提高土壤含水量预测精度,基于物联网监测数据,提出了粒子群算法(PSO)优化BP神经网络的土壤含水量预测方法。首先应用主成分分析法筛选出影响土壤含水量的关键影响因子,然后构建8-5-1的BP神经网络拓扑结构,应用粒子群算法优化BP神经网络的初始权值和阈值。结果表明:与传统BP神经网络相比,新模型优化了网络结构,避免了陷入局部最优解,具有良好的预测效果;模型的评价指标平均绝对误差、平均绝对百分误差、误差均方根分别为0.259 2、0.010 5和0.135 6,与单一BP神经网络相比,预测精度更高,可满足实际的土壤含水量预测的需要。     

Precipitation forecasting by large-scale climate indices and machine learning techniques

Global warming is one of the most complicated challenges of our time causing considerable tension on our societies and on the environment. The impacts of global warming are felt unprecedentedly in a wide variety of ways from shifting weather patterns that threatens food production, to rising sea levels that deteriorates the risk of catastrophic flooding. Among all aspects related to global warming, there is a growing concern on water resource management. This field is targeted at preventing future water crisis threatening human beings. The very first stage in such management is to recognize the prospective climate parameters influencing the future water resource conditions. Numerous prediction models, methods and tools, in this case, have been developed and applied so far. In line with trend, the current study intends to compare three optimization algorithms on the platform of a multilayer perceptron (MLP) network to explore any meaningful connection between large-scale climate indices (LSCIs) and precipitation in the capital of Iran, a country which is located in an arid and semi-arid region and suffers from severe water scarcity caused by mismanagement over years and intensified by global warming. This situation has propelled a great deal of population to immigrate towards more developed cities within the country especially towards Tehran. Therefore, the current and future environmental conditions of this city especially its water supply conditions are of great importance. To tackle this complication an outlook for the future precipitation should be provided and appropriate forecasting trajectories compatible with this region's characteristics should be developed. To this end, the present study investigates three training methods namely backpropagation (BP), genetic algorithms (GAs), and particle swarm optimization (PSO) algorithms on a MLP platform. Two frameworks distinguished by their input compositions are denoted in this study: Concurrent Model Framework (CMF) and Integrated Model Framework (IMF). Through these two frameworks, 13 cases are generated: 12 cases within CMF, each of which contains all selected LSCIs in the same lead-times, and one case within IMF that is constituted from the combination of the most correlated LSCIs with Tehran precipitation in each lead-time. Following the evaluation of all model performances through related statistical tests, Taylor diagram is implemented to make comparison among the final selected models in all three optimization algorithms, the best of which is found to be MLP-PSO in IMF.     

羊肚菌营养袋制作原料的化学成分分析及配方优化

为优化羊肚菌营养袋的原料组成与配比,以食药用菌栽培基质中常用的4种秸秆及谷壳、麦粒、麦麸,通过主成分分析归纳各原料的营养组成属性,设计出9个营养袋配方进行栽培试验,比较出菇产量,得出高产营养袋原料组合为谷壳和麦粒;再以谷壳与麦粒按11种不同的重量比混合制成营养袋进行栽培试验,综合考量制作成本、出菇产量、经济效益等因素后,最终得到高产高效的羊肚菌营养袋配方(重量比)为谷壳19%、麦粒79%、石灰1%、石膏1%。     

优化预处理及脱毒工艺以制备玉米芯半纤维素水解液

为了降低玉米芯半纤维素水解液中的乙酸、糠醛和酚类等有毒物质含量,使可利用糖类含量增加。本研究以玉米芯为原料制备水解液,对预处理及脱毒工艺进行优化,并利用高效液相色谱(HPLC)检测优化效果。结果表明,10~20目的玉米芯在10%氨水浸泡24 h后,可将乙酸和酚类物质的脱除率,分别提高至93.4%和32.3%,而糠醛的含量也大大降低。经过真空浓缩、CaO脱毒以及2%活性炭吸附后,使有毒物质含量再次降低,此时的水解液可完全用于菌株的发酵试验,达到了去除的目的。本文所得到的最佳水解液处理步骤,其结果符合菌株发酵用标准,说明水解液处理方式的不同,直接影响着水解液的制备。这为研究和利用木质纤维素等可再生资源提供了思路,也为发酵生产奠定了理论基础。