关于(QU)型模糊拓扑群的直积

研究(QU)型模糊拓扑群族直积,证明了任意(QU)型模糊拓扑群族的直积仍是(QU)型模糊拓扑群;研究了(QU)型模糊拓扑群族直积的模糊单位元之重域基的结构,得到了(QU)型模糊拓扑群族直积的一些重要性质.     

Smooth拓扑空间的Moore-Smith收敛理论

以远域为工具讨论了smooth拓扑空间的Moore-Smith收敛理论.     

神经网络在成组技术方面的应用

阐述了成组技术及其在高级制造技术中的作用，在此基础上描述了神经网络在零件编码分类系统中的应用以及用神经网络设计制造单元的方法。     

模糊神经网络在复合地基沉降量预测中的应用

复合地基后期沉降变形对于建筑物设计及安全具有重要意义,针对通过长期沉降观测以得到复合地基的最终沉降需要耗费较多资源的问题,提出了一种基于模糊神经网络的预测方法.该方法考虑沉降变化过程有较大的随机性和模糊性,直接将样本数据进行模糊化,所得的模糊数代表了样本点集与控制点集中各分量之间的相关度,并依此建立模糊BP神经网络进行学习和估算.实验结果表明了该方法对沉降进行预测是可行与有效的,且在相对误差的有效控制方面优于BP网络方法与灰色方法.     

成本性态法在分析可比产品成本降低计划完成情况中的应用

本文根据成本性态法的思路．分析了影响可比产品成本降低额和降低率变动的因素，重点从理论上论证了产品品种结构的影响，并且合理地把单纯产量和品种结构对可比产品成本降低额（率）的影响分离开来．     

Solving multiple-objective problems in the objective space

Projection and relaxation techniques are employed to decompose a multiobjective problem into a two-level structure. The basic manipulation consists in projecting the decision variables onto the space of the implicit tradeoffs, allowing the definition of a relaxed multiobjective master problem directly in the objective space. An additional subproblem tests the feasibility of the solution encountered by the relaxed problem. Some properties of the relaxed problem (linearity, small number of variables, etc.) render its solution efficient by a number of methods. Representatives of two different classes of multiobjective methods [the Geoffrion, Dyer, Feinberg (GDF) method and the fuzzy method of Baptistella and Ollero] are implemented and applied within this context to a water resources allocation problem. The results attest the computational viability of the overall procedure and its usefulness for the solution of multiobjective problems.This work was partially sponsored by grants from CNP_q and FAPESP, Brazil. The authors are indebted to the anonymous reviewers for their valuable comments.     

关于Fuzzy聚类分析及其在脊髓灰质炎中的应用

本文用Fuzzy数学的观点探讨了Fuzzy聚类分析，并通过对脊髓灰质炎病毒抗体水平的Fuzzy聚类分析，获得了良好的聚类效果，为该项问题的研究提供了科学依据。     

模糊集合论在矿山控制网布设和图纸质量评定中的应用

应用模糊数学方法研究和处理矿山测量中存在的具有“模糊性”的问题。例如控制网布设方案及矿山测量图纸质量的综合评判。它能更准确地描述用精确数学模型难以描述的问题。     

A neuro-fuzzy system for X-ray spectra interpretation

A decision scheme for the interpretation of spectra from wavelength dispersive X-ray fluorescence spectrometry is described that encompasses elements from three areas of artificial intelligence: fuzzy logic, rule based expert systems and neural net technology.After transforming the recorded spectra to line spectra by appropriate background correction a reasoning scheme is applied that takes into account not only the observed spectra, but also the recording conditions and prior spectroscopic information regarding the relative emission probabilities and the usefulness of the different lines for the purpose of element identification. The latter is done on the basis of a previously described scheme to compute conditional a posteriori Bayes probabilities for a mean matrix. These different pieces of information are then assembled into a battery of fuzzy rules. The importance of the rules as well as the importance of the X-ray lines is determined in a training process, similar to the one in a feedforward back-propagation network.To further stabilize the results this network is pruned in a second training cycle. This, however, had little effect on the quality of interpretation.The advantages of this approach to the interpretation of X-ray spectra over older ones are numerous: the system adapts itself to better interpret spectra that are of greater importance to a laboratory as these are better represented in the training set; the fuzzy logic is capable of working with incomplete and uncertain knowledge, and the neural network results based on these fuzzy rules is readily interpretable by the X-ray spectroscopist as every rule can be expressed also in natural language as in any classical rule based system.On leave from Silesian University, Katowice, Poland     

Fuzzy Symmetries for Linear Molecules and their Molecular Orbitals

In this paper, the fuzzy symmetry of some prototypical linear molecules has been analyzed. The results show that some molecular orbitals (MOs) are less symmetrical but some others are more symmetrical than the molecular skeleton, which the MOs correspond to. The membership functions of space inversion for MOs are closely related to the chemical characteristics of the MOs. Sometimes, although the symmetry of a molecular skeleton is not obvious, however that of some MO is quite obvious. The membership functions of the fuzzy inversion symmetry depend on the choice of the position of the center of inversion. As compared to those of diatomic molecules and linear tri-atomic molecules, the linear polyatomic molecules in which a distinctive fuzzy symmetry of space translation may exist, and thus a significant effect on their properties can be expected.