基于模糊因素的载人航天器乘员舱内人-机界面工效学评价研究

载人航天器乘员舱内人－机界面的工效学评价是决定能否进行载人空间飞行的重要依据之一，由于人－机界面本身的复杂性，使得对其评价有一定的难度。本文在模糊理论的基础上，首先对舱内人－机界面工效学评价各参数进行随机模糊分析，据此建立工效学模糊综合评价模型，最后进行了实例研究。结果表明，对于同一个评价对象，应用该方法更能接近实际。     

关于模糊严格偏好关系的传递性

给定一个模糊关系,Ovchinnikov和Roubens引进了非常一般的模糊严格偏好关系定义,本文将详细讨论该偏好关系的弱传递性,一致性,强传递性以及非循环性等传递性有关的性质。     

前苏联和俄罗斯模糊理论研究与应用情况概述

对前苏联20世纪80年代及苏联解体后俄罗斯20世纪90年代的模糊理论研究与应用情况作了概述,列举了在人工智能认知的模糊原理、信息论的模糊性和模糊空间、随机模糊规划、工业用综合模糊控制系统等领域的研究成果,并列出90多篇（部）俄文文献资料。     

Fuzzy幂群的基数及表示

研究Fuzzy幂群^[2]中元素的基数,证明这种Fuzzy幂群并非Zadeh意义的Fuzzy子群,而且可以用一分明群表示,给出有限群上Fuzzy幂群的正则表示,并讨论Fuzzy幂群的同态性质。     

Hutton一致结构的点式处理

从点一集映射出发给出通常一致结构的等价刻画,以此为基础在Ｆｕｘｘｙ格上引入一种（拟）一致结构,它是Ｈｕｔｔｏｎ（拟）一致结构的相应简化。     

The opportunity cost of mean–variance choice under estimation risk

Mean–variance portfolio choice is often criticized as sub-optimal in the more general expected utility framework. It is argued that the expected utility framework takes into consideration higher moments ignored by mean variance analysis. A body of research suggests that mean–variance choice, though arguably sub-optimal, provides very close-to-expected utility maximizing portfolios and their expected utilities, basing its evaluation on in-sample analysis where mean–variance choice is sub-optimal by definition. In order to clarify this existing research, this study provides a framework that allows comparing in-sample and out-of-sample performance of the mean variance portfolios against expected utility maximizing portfolios. Our in-sample results confirm the results of earlier studies. On the other hand, our out-of-sample results show that the expected utility model performs worse. The out-of-sample inferiority of the expected utility model is more pronounced for preferences and constraints under which in-sample mean variance approximations are weakest. We argue that, in addition to its elegance and simplicity, the mean–variance model extracts more information from sample data because it uses the covariance matrix of returns. The expected utility model may reach its optimal solution without using information from the covariance matrix.     

-Difference sequence spaces of fuzzy numbers

In this paper, using the difference operator of order m and an Orlicz function, we introduce and examine some classes of sequences of fuzzy numbers. We give the relations between the strongly Cesàro type convergence and statistical convergence in these spaces. Furthermore, we study some of their properties like completeness, solidity, symmetricity, etc. We also give some inclusion relations related to these classes.     

一类特殊的Fuzzy局部凸空间

文中给出了Ｆｕｚｙ有界型空间的定义，在此基础上，讨论了Ｆｕｚｙ有界型空间的等价定理，最后证明了Ｑ－Ｃ_ＩＦｕｚｙ局部凸空间是有界型的．     

Max—min神经网络的一种有效学习算法

本文在Ａ．Ｂｌａｎｃｏ等人的算法的基础上，提出了ｍａｘ－ｍｉｎ神经网络的一种改进了的反馈学习算法，严格证明了该算法的迭代收敛性，理论分析及实例计算结果均表明，本文算法具有算法简单，收敛速度快，输出误差小等显著特点。     

A learning process for fuzzy control rules using genetic algorithms

The purpose of this paper is to present a genetic learning process for learning fuzzy control rules from examples. It is developed in three stages: the first one is a fuzzy rule genetic generating process based on a rule learning iterative approach, the second one combines two kinds of rules, experts rules if there are and the previously generated fuzzy control rules, removing the redundant fuzzy rules, and the thrid one is a tuning process for adjusting the membership functions of the fuzzy rules. The three components of the learning process are developed formulating suitable genetic algorithms.