Molecular Diffusion Coefficients of Organic Compounds in Water at Different Temperatures

Molecular (or tracer) diffusion coefficient data were obtained for 2-naphthol, benzoic acid, salicylic acid, camphor, and cinnamic acid in water at temperatures that differ significantly from ambient value. Experimental values were determined for the dissolution of 2-naphthol in water at 283 to 368 K, of benzoic acid in water at 283 to 338 K, of salicylic acid in water at 283 to 343 K, of camphor in water at 283 to 318 K, and of cinnamic acid in water at 283 to 318 K. Empirical correlations are presented for the prediction of molecular diffusion coefficient over the entire range of temperatures studied, and they are shown to predict the obtained data with very good accuracy.     

模糊技术的发展及在相关领域中的应用

本文介绍了模糊技术的发展和现状，以及在相关领域中的应用情况，并且讨论了模糊技术在我国的产业化方向等问题。     

利用模糊评判方法确定张东构造油藏储量计算的可靠程度

张巨河油田张东构造地处大港滩海交接处,海域部分探井少.目前用油藏描述方法计算的探明储量,其落实程度备受关注.储量落实程度的评价是一个多因素综合评判问题,而且这些因素还分属不同层次.模糊综合评判是应用较为广泛的模糊数学方法之一.该方法建立的综合评判涉及三个要素,即因素集、评判集和单因素评判,由此所构造的模糊评判关系是模糊综合评判的基础.本文用该方法对张东构造沙二段油藏的探明储量落实程度作了尝试性评价.     

焊前处理方式对LF6铝合金扩散焊的影响

利用Ｇｌｅｅｂｌｅ－１５００热／力模拟试验机，研究了ＬＦ６铝合金的扩散焊工艺，通过对焊接温度、压力、时间的调整和选用不同的料前处理方法，确定了最佳的扩散规范，研究结果表明：在一定的温度和时间范围内，ＬＦ６５铝合金扩散焊接头的剪切哟度随焊接温度和时间的增加而提高；化学浸蚀法比机械打磨法能更有效的去除铝合金表面的氧化膜；在现有试验条件下，得到ＬＦ６铝合金扩散焊的最佳规范参数，搭接试扩散焊接头的剪切强度     

Macroscopic model for multispecies ion-exchange kinetics

A model for multispecies ion-exchange kinetics based on the Nernst-Planck equation is suggested. It is analyzed in comparison with the “locally-determinate” model described by Hwang and Helfferich [1]. The model makes possible simple computation. The conditions for the occurrence of unusual kinetic curves with a maximum are clarified. The proposed model is developed for different types of kinetic problems and verified by the experimental investigation of a kinetics in ternary systems.     

A design and analysis of objective function-based unsupervised neural networks for fuzzy clustering

Fuzzy clustering has played an important role in solving many problems. In this paper, we design an unsupervised neural network model based on a fuzzy objective function, called OFUNN. The learning rule for the OFUNN model is a result of the formal derivation by the gradient descent method of a fuzzy objective function. The performance of the cluster analysis algorithm is often evaluated by counting the number of crisp clustering errors. However, the number of clustering errors alone is not a reliable and consistent measure for the performance of clustering, especially in the case of input data with fuzzy boundaries. We introduce two measures to evaluate the performance of the fuzzy clustering algorithm. The clustering results on three data sets, Iris data and two artificial data sets, are analyzed using the proposed measures. They show that OFUNN is very competitive in terms of speed and accuracy compared to the fuzzy c-means algorithm.     

EXTENSION OF THE RELATIONAL DATABASE AND ITS ALGEBRA WITH ROUGH SET TECHNIQUES

This paper describes a database model based on the original rough sets theory. Its rough relations permit the representation of a rough set of tuples not definable in terms of the elementary classes, except through use of lower and upper approximations. The rough relational database model also incorporates indiscernibility in the representation and in all the operators of the rough relational algebra. This indiscernibility is based strictly on equivalence classes which must be defined for every attribute domain. There are several obvious applications for which the rough relational database model can more accurately model an enterprise than does the standard relational model. These include systems involving ambiguous, imprecise, or uncertain data. Retrieval over mismatched domains caused by the merging of one or more applications can be facilitated by the use of indiscernibility, and naive system users can achieve greater recall with the rough relational database. In addition, applications inherently “rough” could be more easily implemented and maintained in the rough relational database.     

模糊自适应的高超飞行器控制与干扰

针对具有超大飞行马赫数、超宽飞行包络、飞行环境复杂等特点的高超声速飞行器,提出了基于模糊自适应的高超飞行器高度控制方法,分别设计了高度和速度控制器.针对所设计的控制器,分析了气动干扰力矩、测量噪声、舵机干扰、气动参数不确定性和飞行器模型参数不确定性对飞行器高度控制和速度控制效果的影响,然后又分析了综合考虑以上干扰和不确定性对飞行器高度控制和速度控制效果的影响.仿真结果表明,对各种干扰和不确定性,所设计的控制器速度和高度控制有较好的跟踪性和鲁棒性,达到了满意的效果.     

Adaptive fuzzy decentralized control for nonlinear large-scale systems based on high-gain observer

An adaptive fuzzy decentralized backstepping output-feedback control approach is proposed for a class of nonlinear large-scale systems with completely unknown functions,the interconnections mismatched in control inputs,and without the measurements of the states.Fuzzy logic systems are employed to approximate the unknown nonlinear functions,and an adaptive high-gain observer is developed to estimate the unmeasured states.Using the designed high-gain observer,and combining the fuzzy adaptive control theory with backstepping approach,an adaptive fuzzy decentralized backstepping output-feedback control scheme is developed.It is proved that the proposed control approach can guarantee that all the signals of the closed-loop system are semi-globally uniformly ultimately bounded(SUUB),and that the observer errors and the tracking errors converge to a small neighborhood of the origin by appropriate choice of the design parameters.Finally,a simulation example is provided to show the eectiveness of the proposed approach.