非线性时间序列数据中的关联维提取

本文将混沌方法引入具有非线性时间序列的降雨量分析。首先对有关混沌及关联维的概念作简单介绍,在确定降雨量数据具有混沌特征后,对其进行关联维提取,得到颇具意义的结果。     

Time series analysis of wind speed using VAR and the generalized impulse response technique

This research examines the interdependence in time series wind speed data measured in the same location at four different heights. A multiple-equation system known as a vector autoregression is proposed for characterizing the time series dynamics of wind. Additionally, the recently developed method of generalized impulse response analysis provides insight into the cross-effects of the wind series and their responses to shocks. Findings are based on analysis of contemporaneous wind speed time histories taken at 13, 33, 70 and 160 ft above ground level with a sampling rate of 10 Hz. The results indicate that wind speeds measured at 70 ft was the most variable. Further, the turbulence persisted longer at the 70-ft measurement than at the other heights. The greatest interdependence is observed at 13 ft. Gusts at 160 ft led to the greatest persistence to an “own” shock and led to greatest persistence in the responses of the other wind series.     

关于移动平均过程两系数的推导

对经济预测方法中两公式给出了证明，两公式的系数被显式推导出来，这两个公式是时间序列模型公式，广泛用于经济预测之中，但文献上很难找到推导过程，本文的证明是基本的，无需高深数学知识即可理解．     

Identification environment and robust forecasting for nonlinear time series

In this paper, the methods of time series for nonlinearity are briefly surveyed, with particular attention paid to a new test design based on a neural network specification. The proposed integrated expert system contains two main components: an identification environment and a robust forecasting design. The identification environment can be viewed as a integrated dynamic design in which cognitive capabilities arise as a direct consequence of their self-organizational properties. The integrated framework used for discussing the similarities and differences in the nonlinear time series behavior is presented. Moreover, its performance in prediction proves to be superior than the former work. For the investigation of robust forecasting, we perform a simulation study to demonstrate the applicability and the forecasting performance.     

一种新的时变大系统递阶控制求解方法

研究了一种新的大系统求解方法,利用Taylor级数的性质,将大系统时变递阶控制问题 转化为代数方程的求解问题.该方法简单,易于编成计算机程序.算例表明了它的有效性.     

非线性动态系统“黑箱”建模方法的研究

本文研究弱非线性动态系统“黑箱”建模的理论和方法，并简要给出根据此方法建模的结果。     

THE RECURSIVE FITTING OF SUBSET VARX MODELS

Abstract. A vector time series model of the form A(L)y(t) + B(L)x(t) =ε(t) is known as a vector autoregressive model with exogenous variables (VARX model) and involves a regressand vector y(t) and a regressor vector x(t). This paper provides a method for the recursive fitting of subset VARX models. It suggests the use of ascending recursions in conjunction with an order selection criterion to choose an 'optimum' subset VARX model.     

报纸媒介系列广告形成特点与设计方式分析

无时间、地点限制反复刺激是报纸媒介系列广告的主要特点。因此,报纸媒介系列性广告在形成方式上具有其特有的时间性与空间性特点;而在广告的表现方式上则通常运用同类并列型、层次递进型、悬念升级型三种系列性设计方式来表现广告主题。     

数据挖掘课程案例教学研究

数据挖掘是一门交叉性学科,是情报学专业的重要课程之一。它主要介绍数据挖掘的基本概念、原理、方法和技术,涉及多个学科和算法因而教学难度较大。由于数据挖掘学科交叉性强涉及的挖掘方法和相关算法多并繁杂,造成学生对数据挖掘的整体工作流程缺乏了解形成“不识庐山真面目只缘身在此山中”现象。文中以时间序列服装销售额预测挖掘项目为教学案例让学生首先掌握数据挖掘的标准流程,重点讲解用到的相关挖掘方法和算法及其在实际挖掘环境中的开发方法,达到“会当I临绝顶一览众山小”的教学目标。通过教学实践教学效果良好。     

高压电气设备支架串联体系地震响应半解析法

通过论述高压电气设备支架串联体系地震响应半解析法的运算过程,说明地震响应半解析法对于电力系统防震工作的帮助。