丝瓜幼苗的吸水规律

以葫芦科1年生攀缓植物丝瓜幼苗为材料,研究了它在低浓度不同种类盐中的吸水规律和在不同浓度的KCl溶液中以总吸水倍率和叶子中脯氨酸质量分数以及培养外液渗透压变化作为测定指标,从渗透压作为丝瓜幼苗时期吸水动力的角度,探讨其吸水动力学变化及生长规律.结果表明:低浓度(0.001 0 mol/L)各种盐对丝瓜幼苗的总吸水倍率的影响为LiCl＞KCl》二次蒸馏水＞NaCl;不同浓度(0～0.014 0 mol/L)KCl影响下丝瓜幼苗总吸水倍率、脯氨酸质量分数、培养液进入植物体内的粒子数随KCl浓度成峰形变化,并且三者的变化基本吻合.KCl浓度为0.001 0 mol/L时脯氨酸质量分数达最低值,0.004 0 mol/L时脯氨酸的质量分数达最高值,在无盐和高盐环境下脯氨酸的大量积累是植物细胞的适应性反应,其质量分数的高低不宜作为丝瓜的抗盐性指标.脯氨酸质量分数与进入植物体内粒子数变化正相关,并拟合出关系式w=k0+keR0n,w为脯氨酸的质量分数,n为进入植物体内的粒子数,k0,k,R0均为常数.本研究为探讨植物体中脯氨酸积累的生理作用及意义提供参考.     

基于模糊点数据的线性回归分析

在经典回归分析理论中,假定训练数据是独立同分布的随机样本,并且在回归方程的构建中是同等对待的.然而,在许多实际问题中,训练数据的作用是不同的;通常有些训练数据比其它数据可能更为重要,因而不同的训练数据对曲线拟合的贡献应该不同.人们要求重要的训练数据对曲线拟合做出更大的贡献.实现这一目标的策略是给每个训练数据赋予一个置信权重并且重新推导了经典的最小二乘回归方法,分析了它们的统计性质.受文[1]的启发,将这里的样本称为模糊点样本数据.     

一种新的模糊神经网络删剪策略

模糊规则的数量直接决定模糊神经网络结构的复杂度和效率.基于神经网络自构行学习(NNSCL)算法,用共轭剃度预条件正则方程算法求取删除隐层神经元后的剩余权值,得到改进的NNSCL-1算法.将此算法应用到模糊神经网络的规则推理层,可以极大地优化网络的规则及结构,并且结构优化后不需要重新训练也能保持网络的精确度和泛化能力.仿真结果显示了此算法的有效性和可行性.     

关于Erlang(n)风险过程的破产概率

考虑一个连续时间的风险模型,其中索赔时间间隔服从Erlang(n)分布,而且风险过程的调节系数不存在,本文给出了破产概率的渐近估计.     

中国无缝钢管技术装备的发展对策探讨

结合中国无缝钢管技术装备发展的问题,从充分发挥现有先进装备的特长和作用进行结构调整等方面探讨了中国无缝钢管技术装备的发展对策。     

北约体制的结构性缺陷与美欧的互动调整

北约体制是以美国为主导,以欧洲国家为主体,以欧洲安全事务为主要内容的结构形式,主导国家与主体国家的分离是形成结构性缺陷的根本原因。在冷战后成员利益出现分化时,这种缺陷凸显,井严重威胁到现行北约体制。为了维护北约体制的存续,美、欧双方基于自身利益和实力都进行了深刻地调整,并逐渐形成北约未来体制模式和制度框架。     

四次B-样条法构造国债收益率曲线

随着我国国债期限结构的不断完善,使用科学的方法构造国债收益率曲线具有重要意义。文章用一组B-样条基的线性组合逼近贴现函数,用回归技术得出最优参数,从而进一步得到国债即期收益率曲线;并用上海证券交易所数据构造出我国即期国债收益率曲线。     

Unobserved components in ARCH models: An application to seasonal adjustment

The paper deals with unobserved components in ARIMA models with GARCH errors, in the context of an actual application, namely seasonal adjustment of the monthly Spanish money supply series. The series shows clear evidence of (moderate) non-linearity, which does not disappear with simple outlier correction. The GARCH structure explains reasonably well the non-linearity, and this explanation is robust with respect to the GARCH specification. We look at the time variation of the standard error of the adjusted series estimator and show how it can be measured. Next, we look at the implications this variation has on short-term monetary control. The non-linearity seems to have a small effect in practice. It is further seen that the conditional variance of the GARCH process may, in turn, be decomposed into components. In fact, the conditional variance of the money supply series is the sum of a weak linear trend, a strong non-linear seasonal component, and a moderate non-linear irregular component. This information has policy implications: for example, there are periods in the year when policy can be more assertive because information is more precise. Finally, looking at the non-linear components of the money supply it is seen how linear combinations of non-linear series can produce series that behave linearly.     

取水监测数据的奇异值识别与修正策略

提高水资源监测数据的真实性与完备性是国家水资源监控能力建设的重要内容.本文基于当前国家水资源监控数据的实际统计状况,提出采用小波变换模极大值的方法实现对取用水监测数据的降噪和奇异值的挖掘,并将辨识出的奇异值进行剔除处理后的监测数据序列作为粒子群-最小二乘支持向量机模型的训练样本,进而根据拟合函数对奇异值进行修正的策略.通过对重点取用水户的取用水监测数据进行实证研究结果发现,利用小波变换模极大值可较大限度地保留取用水监测数据的原始信息,并实现对其中变动幅度偏大数据的分离,可有效降噪并观测取用水监测数据的内在变化规律;同时借助相对误差可进一步挖掘监测数据中存在的奇异值,且辨识效果要好于传统统计方法;而粒子群-最小二乘支持向量机模型对取用水监测数据的样本拟合要比普通最小二乘支持向量机、曲线拟合等方法更为有效,运用该方法修正的取用水监测数据奇异值更加符合实际取用水需求的特点.     

Forecasting with Micro Panels: The Case of Health Care Costs

Micro panels characterized by large numbers of individuals observed over a short time period provide a rich source of information, but as yet there is only limited experience in using such data for forecasting. Existing simulation evidence supports the use of a fixed‐effects approach when forecasting but it is not based on a truly micro panel set‐up. In this study, we exploit the linkage of a representative survey of more than 250,000 Australians aged 45 and over to 4 years of hospital, medical and pharmaceutical records. The availability of panel health cost data allows the use of predictors based on fixed‐effects estimates designed to guard against possible omitted variable biases associated with unobservable individual specific effects. We demonstrate the preference towards fixed‐effects‐based predictors is unlikely to hold in many practical situations, including our models of health care costs. Simulation evidence with a micro panel set‐up adds support and additional insights to the results obtained in the application. These results are supportive of the use of the ordinary least squares predictor in a wide range of circumstances. Copyright © 2016 John Wiley & Sons, Ltd.