电流互感器二次线圈串并联使用的误差分析

针对电磁式电流互感器的二次线圈串联或并联使用 ,本文进行了误差分析 ,并得出结论 :串联使用提高精度 ,但带负载能力有所降低 ;并联使用带负载能力提高 ,但精度有所降低     

具不同变化规律的时间序列建模方法

本文对具不同变化规律的时间序列详细介绍了三种建模方法:虚拟变量法,分段拟合法和样条函数法,并给出实例加以说明和比较.     

Forecasting time series with increasing seasonal variation

Four options for modeling and forecasting time series data containing increasing seasonal variation are discussed, including data transformations, double seasonal difference models and two kinds of transfer function-type ARIMA models employing seasonal dummy variables. An explanation is given for the typical ARIMA model identification analysis failing to identify double seasonal difference models for this kind of data. A logical process of selecting one option for a particular case is outlined, focusing on issues of linear versus non-linear increasing seasonal variation, and the level of stochastic versus deterministic behavior in a time series. Example models for the various options are presented for six time series, with point forecast and interval forecast comparisons. Interval forecasts from data-transformation models are found to generally be too wide and sometimes illogical in the dependence of their width on the point forecast level. Suspicion that maximum likelihood estimation of ARIMA models leads to excessive indications of unit roots in seasonal moving-average operators is reported.     

Recursive estimation and forecasting of non-stationary time series

The paper presents a unified, fully recursive approach to the modelling and forecasting of non-stationary time-series. The basic time-series model, which is based on the well-known ‘component’ or ‘structuraL’ form, is formulated in state-space terms. A novel spectral decomposition procedure, based on the exploitation of recursive smoothing algorithms, is then utilized to simplify the procedures of model identification and estimation. Finally, the fully recursive formulation allows for conventional or self-adaptive implementation of state-space forecasting and seasonal adjustment. Although the paper is restricted to the consideration of univariate time series, the basic approach can be extended to handle explanatory variables or full multivariable (vector) series.     

Estimation procedures for structural time series models

A univariate structural time series model based on the traditional decomposition into trend, seasonal and irregular components is defined. A number of methods of computing maximum likelihood estimators are then considered. These include direct maximization of various time domain likelihood function. The asymptotic properties of the estimators are given and a comparison between the various methods in terms of computational efficiency and accuracy is made. The methods are then extended to models with explanatory variables.     

广义试验总时间变换序的几个性质

研究了广义试验总时间(generalized total time on test,简记为GTTT)变换序与及其寿命分布类IFR(increasing failure rate)、DFR(decreasing failure rate)的关系;获得了广义试验总时间变换序关于最小样本的封闭性与关于最大样本的逆封闭性．     

正弦级数L~1可积性与Móricz结果

本文建立了正弦级数(S_T)的例子,系数α_n→0,{α_n}∈(?)∩(?),但{α_n}(?),以及指出存在(S_T),α_n→0,{α_n}∈(?),‖S_n-g‖_1→0,但α_nIogn不趋于零。     

工科《大学物理》教学探讨

从学生实际情况和专业特点出发,提出教学改革方法与手段,力求建立起一套提高学生学习能力的教学体系,激发学生学习兴趣和学习动机,从而保证教学质量,提高教学效果,为后续的课程学习打下基础．     

复模糊值函数级数的广义一致收敛和亚一致收敛

利用模糊数的序关系和分解定理讨论了复模糊值函数级数收敛性,得出了复模糊值函数级数收敛、一致收敛、正则收敛、广义一致收敛、亚一致收敛的条件及一致收敛、广义一致收敛和正则收敛的关系准则。     

福建省区域物流与区域经济的实证研究

福建作为中国东部沿海地区经济最具活力的地区之一,通过大力发展现代区域物流业,促进了区域经济的增长,同时,经济的增长也带动了区域物流的发展.本文将采用误差修正模型及格兰杰因果检验,通过对1978～2010年福建省的经济指标时间序列进行协整分析,探讨福建GDP、物流产值、货物周转量、物流里程的协整关系,从而得出福建区域物流与区域经济增长之间的互动效应.本文发现区域物流的发展水平与区域经济增长存在长期均衡关系.