结构模态参数的时序分析(ARMAV模型)识别法

本文简述了用时间序列分析(ARMAV 模型)识别结构模态参数的原理,对建模方法进行了分析,并对建模分析中至关重要的初值选择问题进行了讨论,提出了一种有效的初值的选取方法;在模拟计算部分中,用 Wilson-θ积分法模拟了一个三个自由度的振动和低信噪比、大阻尼振动和密集模态等复杂情形,对用时序方法(ARMAV 模型)识别模态参数的能力进行了检验;最后通过对实验数据进行有效的预处理后,用时序方法(ARMAV 模型)识别出一个真实结构(圆盘)的第一、二阶模态参数,并得到结构的完整振型.     

A system of metrological assurance of measurement quality for the determination of chemical composition of light alloys and superalloys

 The paper covers the main principles of setting up and the function of the Russian system of metrological assurance of analytical measurements for the production of light alloys and superalloys. Received: 20 October 1998 / Accepted: 9 November 1998     

模糊分析计算中的结构元方法

提出模糊结构元的概念，研究模糊结构元的性质，给出模糊数和模糊值函数的结构元表现定理。利用模糊数和模糊值函数的结构元表现形式，使得过去必须依赖扩张原理和表现定理来刻画的模糊数运算、模糊值函数的微积分运算等变得更加简单与直观。     

The ‘Temperature Integral’ — Its use and abuse

This paper first reviews the history of the temperature dependence of reaction rate in reaction kinetics. The various equations which are in use today for expressing this dependence were delineated by van't Hoff almost one hundred years ago. Since an exponential form best describes this dependence for most thermal analysis reactions and, due to the fact that the simple Arrhenius equation (with a temperature-independent preexponential factor) has traditionally been used for this purpose, the mathematically intractable temperature integral often has become a necessary evil in the analysis of thermal analysis kinetics. Methods which avoid the temperature integral in kinetics analysis are discussed. The merits of various evaluations and approximations for the temperature integral are described and assessed in this paper.     

平衡随机模型中方差分量的非负估计

众所周知, 对于平衡随机模型, 方差分量的方差分析估计为一致最小方差无偏估计. 本文基于方差分量的方差分析估计, 构造了一个二次不变估计类, 它包含了一些常用重要估计. 证明了该估计类在一定条件下在均方误差意义下一致优于方差分析估计, 并在此估计类基础上, 给出了方差分量的两种非负估计, 它们在均方误差意义下分别一致优于方差分析估计和限制极大似然估计, 且有显式解、容易计算.     

Ultrasound-assisted extraction and analysis of maidenhairtree polysaccharides

The maidenhairtree polysaccharides (MTPs) have important application prospects. So, the extraction, purification, structure, derivatization and biological activities of polysaccharides from leaves, fruits, and testae of maidenhairtree were disscussed. Polysaccharides were extracted by collaborative extraction methods such as ultrasound-assisted extraction and microwave-assisted extraction. The ultrasound-assisted extraction had higher content and higher efficiency. The structural characteristics and structure-activity relationship of maidenhairtree polysaccharides were studied in order to provide theoretical basis and technical support for the further development and utilization of maidenhairtree polysaccharides.     

An adaptive network based fuzzy inference system–auto regression–analysis of variance algorithm for improvement of oil consumption estimation and policy making: The cases of Canada,United Kingdom,and South Korea

This paper presents an adaptive network based fuzzy inference system (ANFIS)–auto regression (AR)–analysis of variance (ANOVA) algorithm to improve oil consumption estimation and policy making. ANFIS algorithm is developed by different data preprocessing methods and the efficiency of ANFIS is examined against auto regression (AR) in Canada, United Kingdom and South Korea. For this purpose, mean absolute percentage error (MAPE) is used to show the efficiency of ANFIS. The algorithm for calculating ANFIS performance is based on its closed and open simulation abilities. Moreover, it is concluded that ANFIS provides better results than AR in Canada, United Kingdom and South Korea. This is unlike previous expectations that auto regression always provides better estimation for oil consumption estimation. In addition, ANOVA is used to identify policy making strategies with respect to oil consumption. This is the first study that introduces an integrated ANFIS–AR–ANOVA algorithm with preprocessing and post processing modules for improvement of oil consumption estimation in industrialized countries.     

Decomposing profit inefficiency in DEA through the weighted additive model

An issue that has received little attention in the Data Envelopment Analysis literature is the decomposition of profit inefficiency by means of measures that account all sources of technical inefficiency. In this paper we introduce a new way to measure and decompose profit inefficiency through weighted additive models. All our results are derived from a new Fenchel-Mahler inequality using duality theory.     

对主成分分析法三个问题的剖析

从主成分分析法的基本原理入手,针对教学过程中学生对主成分分析法感到费解的三个问题进行了逐一剖析:1.为什么主成分系数是经标准差标准化后原始变量的协方差矩阵的特征向量?2.特征向量正负号如何选取?对进一步的研究如计算综合得分和聚类分析有何影响?3.主成分载荷值是如何得来的?同时指出有些教材在计算主成分得分时混淆了主成分载荷和特征向量的概念,以致造成错误的结果.