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.     

铰接式车辆横向一级倾翻轴的准确位置

通过对铰接式车辆横向一级失稳过程的推导，求得了横向一级倾翻轴的准确位置，它低于过去传统计算方法中的横向一级倾翻轴，本文的理论分析结论不仅可用于分析稳定性，还对设计时铰接点的布置、摆动轴的高低等总体布局具有参考价值。     

Inverse Modeling to Quantify Irrigation System Characteristics and Operational Management

Remotely sensed (RS) data is a major source to obtain spatialdata required for hydrological models. The challenge for thefuture is to obtain besides the more direct observable data(landcover, leaf area index, digital elevation model andevapotranspiration), non-visible data such as soilcharacteristics, groundwater depth and irrigation practices.In this study we have explore the option of using inversemodeling to obtain these non-RS-visible data. For a commandarea in Haryana, India, we applied for the 2000–2001 rabiseason a RS-GIS-combined inverse modeling approach to derivenon-RS-visible data required in the regional application ofhydrological models. A Genetic Algorithm loaded stochasticphysically based soil-water-atmosphere-plant model (SWAP) wasdeveloped for the inverse problem and used in the study. Theresults showed good agreement with the inventoried data suchas soil hydraulic properties, sowing dates, groundwaterdepths, irrigation practices and water quality. The deriveddata could be used to predict the state of the system at anytime in the cropping season, which can be used to evaluateoperational management strategies.     

遗传算法在离心泵叶片优化设计中的应用

对遗传算法在流体机械优化设计中的应用现状作了较为全面的总结；提出了将遗传算法应用于离心泵叶片优化设计中，分析了遗传算法在离心泵优化设计中应用的可行性以及存在的问题；对离心泵优化设计的发展提出了一些新建议和尝试。     

基于径向基神经网络的叶轮轴面投影图优化

为了提高余热排出泵的效率,采用拉丁超立方试验设计方法对叶轮轴面投影图上的前盖板圆弧半径、后盖板圆弧半径、前盖板倾角和后盖板倾角4个几何变量进行35组叶轮方案设计,应用ANSYS CFX 14.5软件对余热排出泵进行定常数值模拟,得到设计工况下的效率,应用径向基神经网络建立效率与轴面投影图的4个几何变量之间的近似模型,最后采用遗传算法对近似模型进行极值寻优,获得最优的轴面投影图几何参数组合。研究结果表明:对比原始泵的数值模拟性能曲线和试验外特性能曲线,两者吻合较好;径向基神经网络能较好地预测泵设计点效率;优化的轴面投影图使得余热排出泵的水力效率提高了6.18个百分点,改善了叶轮内流场特性。因此,叶轮轴面投影图的优化设计方法是可行的。     

基于PPC模型的农机选型与优序关系研究

将投影寻踪（PP）与实数编码的遗传算法（RAGA）相结合，应用到农业机械的选型与优序关系研究中，通过寻求各种机型评价指标的最佳投影方向，将高维数据转换成一维投影指标值，实现对机器样本的分类与排序，从而克服 以往二阶模糊综合评判法及灰色系统评价法中权重取值的人为因素，取得了良好的效果。     

遗传神经网络在温室黄瓜霜霉病预测中的应用

在神经网络结构的优化、连续权重的训练中采用遗传算法的方法对日光温室黄瓜霜霉病进行预测，并对其发生程度进行了拟合，计算值与实际值接近，表明该模型具有良好的预测效果。     

OsGA20ox2不同长度RNAi片段对水稻株高等农艺性状的遗传效应

利用OsGA20ox2基因序列构建不同长度的RNAi片段并导入水稻，获得不同高度的矮化植株。将这些矮化植株与野生型植株回交获得B₁F₂群体，卡方检测表明B₁F₂群体矮秆植株数和高秆植株数符合3∶1比例，表现为矮秆显性的遗传规律。对矮化植株的F₅和B₁F₂群体株高、各茎节间长度和一些主要农艺性状方差分析显示, OsGA20ox2基因的RNAi能显著缩短株高和各节间长度(P<0.05)，RNAi干扰片段越长，使植株株高和节间长度缩短程度越大，可使株高降低24~42 cm，矮化22%~39%。在同一长度的RNAi干扰片段下，倒一节节间长度平均缩短与倒二节节间长度平均缩短非常相近，倒三节和倒四节节间长度平均缩短非常相近，总的缩短程度是倒四节>倒三节>倒二节>倒一节。这种近基部节间长度缩短幅度和比例较大的特点，利于提高水稻的抗倒伏能力，同时上部节间缩短幅度和比例较小，有效地保持合理株高，不使生物产量明显降低，有利于水稻的稳产和高产。OsGA20ox2基因的RNAi不影响如千粒重、结实率、穗长等其他主要农艺性状或影响很小。     

黑色/长梨形樱桃番茄种质的研究利用

以樱桃番茄黑褐色圆形自交系Z1、红黑色长梨形自交系Z2、红色圆形、浅粉红色扁圆形、
橙黄色长椭圆形和黄色圆形等自交系为试材，进行不完全双列杂交配制组合。通过对杂交组合后代的农艺
性状、品质特性和抗病性等的调查研究，探究黑色樱桃番茄种质品质改良和长梨形果形的利用，为今后特
殊果形果色番茄种质的创新利用提供参考。结果表明：樱桃番茄果色黑色性状为隐性性状；亲本为圆形果
或扁圆形果×长梨形果、长椭圆形果×长梨形果时，F₁ 果形分别是椭圆形与长指形。     

贵州野生枇杷资源遗传多样性的ISSR分析

本文采用ISSR标记，构建了贵州39份野生枇杷种质的DNA指纹图谱，并对其遗传多样性进行了评价。结果表明，以筛选出的15条引物进行PCR扩增，获得清晰、重复性好的谱带125条，其中多态性谱带108条，多态性比例为86.4%；应用引物815、825和841的组合，构建了39份枇杷种质的ISSR指纹图谱，可以有效区分所有供试材料；15条引物的谱带数据聚类分析表明，供试种质的遗传相似性系数为0.40~0.98，在相似性系数为0.70时，可将供试种质分成五大类。聚类结果与种质表型相关，与地理分布的相关性不明显。