Using improved neural network model to analyze RSP,NOx and NO2 levels in urban air in Mong Kok,Hong Kong

As the health impact of air pollutants existing in ambient addresses much attention in recent years, forecasting of airpollutant parameters becomes an important and popular topic inenvironmental science. Airborne pollution is a serious, and willbe a major problem in Hong Kong within the next few years. InHong Kong, Respirable Suspended Particulate (RSP) and NitrogenOxides NO_x and NO₂ are major air pollutants due to thedominant diesel fuel usage by public transportation and heavyvehicles. Hence, the investigation and prediction of the influence and the tendency of these pollutants are ofsignificance to public and the city image. The multi-layerperceptron (MLP) neural network is regarded as a reliable andcost-effective method to achieve such tasks. The works presentedhere involve developing an improved neural network model, whichcombines the principal component analysis (PCA) technique and theradial basis function (RBF) network, and forecasting thepollutant levels and tendencies based in the recorded data. Inthe study, the PCA is firstly used to reduce and orthogonalizethe original input variables (data), these treated variables arethen used as new input vectors in RBF neural network modelestablished for forecasting the pollutant tendencies. Comparingwith the general neural network models, the proposed modelpossesses simpler network architecture, faster training speed,and more satisfactory predicting performance. This improvedmodel is evaluated by using hourly time series of RSP, NO_x and NO₂ concentrations collected at Mong Kok Roadside Gaseous Monitory Station in Hong Kong during the year 2000. By comparing the predicted RSP, NO_x and NO₂ concentrationswith the actual data of these pollutants recorded at the monitorystation, the effectiveness of the proposed model has been proven.Therefore, in authors' opinion, the model presented in the paper is a potential tool in forecasting air quality parameters and hasadvantages over the traditional neural network methods.     

无缝钢管局部径向模具塑性成形过程的三维有限元数值模拟

采用大变形弹塑性有限元理论,用DYNA3D(研究版)有限元软件,对无缝钢管局部径向模具塑性成形过程中当凸模的凹槽尺寸与凸模的圆弧半径发生变化时进行了数值模拟研究,得出了对成形钢管表面质量控制具有重要参考价值的结论,解决了成形钢管表面的压痕问题。     

象山港国华电厂强增温海域浮游动物群落结构和多样性的时空特征

为探明电厂强增温海域浮游动物群落结构和多样性的时空特征,于2011年在象山港国华电厂附近海域,采用浮游生物Ⅱ型网(网目160μm)进行10站位2重复的浮游动物季节性采样.结果表明,共识别出62种浮游动物(含幼体),平均丰度为9 531.1 ind.m-3.该海域浮游动物群落主要由桡足类和浮游幼体类组成,且以浮游幼体类为主,比例高达66.6%.相似性分析显示,各月间浮游动物群落结构差异极显著(P<0.01),控制群落结构的优势种有18种,最重要的判别种有瘦尾胸刺水蚤Centropages tenuiremis、大同长腹剑水蚤Oithona similis、伪长腹剑水蚤Oithona fallax、克氏纺锤水蚤Acartia clausi、长尾基齿哲水蚤Clausocalanus furcatus、针刺拟哲水蚤Paracalanus aculeatus和小拟哲水蚤Paracalanus parvus.GLM分析显示,月份间的多样性指数也存在极显著差异(P<0.01),经计算,各多样性指数随水温增加而下降的拐点水温范围为20.31～22.31℃.在断面上,离排水口0.2 km断面(D02)的平均水温比2 km断面高2.16℃.受温度影响,主要优势种如瘦尾胸刺水蚤和大同长腹剑水蚤倾向于向D02断面移动,克氏纺锤水蚤、尤其是大型浮游动物倾向于远离排水口,并向1.2 km断面聚集,使D02断面的种类数最少(33种)、丰度最低(5 522.8 ind.m-3),而1.2 km断面的种类数(53种)和丰度(16 491.0 ind.m-3)最高;同时,D02断面的多样性指数也明显低于其它断面.经线性回归分析,海域增温使多样性指数极显著下降(P<0.01),每增温1℃浮游动物丰富度下降12.3%.     

Specific features of the growth of Scots pine vegetative organs in the forest-steppe zone of Cisbaikalia

The dependence of the annual increment of vegetative organs on air temperature and humidity and the amount of precipitation per phenophase, as well as the period of their growth in Scots pine, were studied in the forest-steppe zone of Cisbaikalia. The multiple effect of variation in environmental conditions on the annual increment of organs increased when precipitation in September of the previous year was taken into account. These factors proved to have a stronger effect on variation in the annual increment of needles (R ² = 0.59, p = 0.00005) than that in the annual ring width (R ² = 0.38, p = 0.0002).     

山区土壤重金属空间插值性能的改进

山区土壤重金属监测中,密集均匀的布点采样困难大,成本高。根据稀疏非均匀样本数据准确预测山区土壤重金属空间分布,对可视化描述检测元素的分布及趋势具有重要意义。基于云南省楚雄市南部山区表层土壤中重金属锰、钒的采样数据,对集成径向基函数神经网络(IRBFANNs)和传统插值方法:反距离(IDW)、普通克里格(OK)、径向基函数神经网络(RBFANNs),进行了不同等级采样密度下的插值性能比较。结果表明,样本点数量减少时,传统预测方法的插值精度都有所下降,而IRBFANNs算法在样本点较少情况下能够保持最好的插值精确度和稳定性,有效改进了空间插值性能。     

星形大分子液晶在气相色谱分析中的应用研究

将首次合成的偶氮苯硅氧烷类星形液晶大分子化合物用于毛细管柱气相色谱固定液 ,在其相转变温度附近具有良好的选择性 ,成功地分离了二甲酚异构体。     

叠氮增塑剂/硝化棉共混物的分子动力学模拟

目的 揭示叠氮增塑剂与硝化棉的相互作用机理,探索叠氮类增塑剂结构与性能间的关系,筛选能量性能和稳定性均较好的叠氮化合物。方法 建立硝化棉(NC)、1,3–二(叠氮乙酰氧基)–2–甲基–2–硝基丙烷(DAMNP)、1,3–双(叠氮乙酰氧基)–2–乙基–2–硝基丙烷(ENPEA)和1,8–二叠氮基–3,6–氧杂辛烷(AZTEGDN)纯物质模型以及NC/DAMNP、NC/ENPEA、NC/AZTEGDN共混物体系的微观分子模型,利用分子动力学模拟(MD)方法,对叠氮增塑剂/硝化棉的微观性质进行预测。分析共混体系的溶度参数、MSD值、结合能、径向分布函数、力学性能和玻璃化转变温度等性能。结果 DAMNP、ENPEA、AZTEGDN与NC之间的溶度参数差值较小。ENPEA与NC的结合能最大,DAMNP次之,AZTEGDN最小。3种增塑剂与NC的相互作用主要为vdW相互作用。加入增塑剂分子可以改善NC的运动能力,由于AZTEGDN的分子结构体积小,改善效果明显。径向分布函数分析结果进一步证明,NC与增塑剂分子间存在较强的氢键作用。结论 添加叠氮增塑剂可以改善NC的运动能力、力学性能,降低NC的玻璃化转变温度,起到了良好的增塑效果。     

2003年夏秋季大气环流异常对西北地区降水的影响

根据2003年6～10月西北地区118站逐日降水资料,对该地区、该时段的大气环流及其对该地区降水的影响进行了分析研究.     

煤层透气性系数的优化和简化计算方法

煤层透气性系数是用以考察保护层开采效果和设计瓦斯抽采系统的重要参数之一,钻孔径向流量法是求取该系数最常用的算法。利用理论推导和图形分析方法,探讨流量准数、时间准数、煤层透气性系数与参数A,B间的关系。在此基础上,针对科研工作和现场管理的实际情况,提出求解透气性系数的2种新算法及其算法流程,并对时间准数-参数A,B函数关系中的间断点问题进行讨论和分析,解决此区间内求解透气性系数相应计算公式等问题。理论和实例分析表明:算法1在不更改最终计算公式和结果的前提下,省去了繁琐的试算过程,既保证了可靠性也优化了计算流程;算法2以稍减精度的代价对计算流程进行进一步的简化,其结果仍有较高精度。