知识库中精确知识的判定算法

研究了知识库中挖掘它所包含的精确知识的方法，给出知识库的相关概念及精确知识的定义，讨论了一种在所定义的知识库中提取并判定精确知识的算法．     

EQUILIBRIUM ALGORITHMS WITH NONMONOTONE LINE SEARCH TECHNIQUE FOR SOLVING THE TRAFFIC ASSIGNMENT PROBLEMS

This paper presents a unified bination algorithms （such as FrankWolfe problems. Global convergence results are framework of the nonmonotone convex comAlgorithm） for solving the traffic assignment established under mild conditions. The line search procedure used in our algorithm includes the nonmonotone Armijo rule, the non- monotone Goldstein rule and the nonmonotone Wolfe rule as special cases. So, the new algorithm can be viewed as a generalization of the regular convex combination algorithm.     

可变分区存储管理方式的模拟

论述了如何用C语言模拟可变分区存储管理方式的过程。形象地展示了操作系统中可变分区存储管理中采用的最佳适应算法的分配与回收过程，达到了理论与实践相联系的目的。     

面向对象数据库"联系_选择"查询操作的优化

综合考虑逻辑因素和选择谓词的选择率、谓词本身的复杂度等物理因素后，给出了“联系_选择”及其拓展“联系_选择_投影”两个重要的复合操作的优化算法，提高了查询的执行效率。     

Seismic 3D Prestack Time Migration on Parallel Computers

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系统结构模型分部的底层要素法

本文从系统的底层要素出发，提出并证明了底层要素存在性、底层要素后果集并集的完全性以及它们在同一部分的充分必要条件，由此导出了系统结构模型分部的算法，实际应用进一步说明了这一方法的有效性。     

一类自适应松弛算法的算法模型

对于一类自适应松弛算法,本文提出了一个算法模型。在一些通常的假定下,证明了该模型生成的序列的收敛性定理。     

Quantitative genetic models of sexual selection

Summary Quantitative genetic models of sexual selection have disporven some of the central tenets of both the handicap mechanism and the sexy son hypothesis. These results suggest that the good genes approach to sexual selection may generally lead to erroneous results.Runaway sexual selection seems possible under a wide variety of circumstances. Quantittive genetic models have revealed runaway processes for sexually selected attributes expressed in both sexes and for attributes of parental care. Furthermore, the runaway could occur simultaneously in a series of populations that straddle an environmental gradient. While the models support the feasibility of runaway processes, empirical studies are needed to evaluate whether runaways actually happen. Estimates of critical genetic parameters are particularly needed, as well as measures of natural and sexual selection acting on the same population.The models also show that sexual selection has tremendous potential to produce population differentiation, particularly in epigamic traits. Differentiation is promoted by indeterminancy of evolutionary outcome, transient differences among populations during the final slow approach to equilibrium, sampling drift among equilibrium populations, and the tendency of sexual selection to amplify geographic variation arising from spatial differences in natural selection. Recent work with two- and three-locus models of sexual selection has produced results that parallel the results of the polygenic models^36–38,58. Thus the feature of indeterminate equilibria (outcome dependent on initial conditions) is common to both types of model.     

The Young-Householder algorithm and the least squares multidimensional scaling of squared distances

It is shown that replacement of the zero diagonal elements of the symmetric data matrix of approximate squared distances by certain other quantities in the Young-Householder algorithm will yield a least squares fit to squared distances instead of to scalar products. Iterative algorithms for obtaining these replacement diagonal elements are described and relationships with the ELEGANT algorithm (de Leeuw 1975; Takane 1977) are discussed. In large residual situations a penalty function approach, motivated by the ELEGANT algorithm, is adopted. Empirical comparisons of the algorithms are given.An early version of this paper was presented at the Multidimensional Data Analysis Workshop, Pembroke College, Cambridge, July 1985. I want to thank Jan de Leeuw and Yoshio Takane for bringing the ELEGANT algorithm to my attention and for clarifying its rationale and notation. My thanks go also to Stephen du Toit for help with the ALSCAL computations reported in Section 7.     

基于SSA-LSTM-GF的混凝土坝变形预测方法

针对混凝土坝变形分析预测的复杂性,应用相空间重构思想和融合建模理念,提出了一种基于SSA-LSTM-GF的混凝土坝变形分析预测方法。SSA-LSTM-GF方法利用奇异谱分析法(SSA)将变形实测数据序列分解为趋势分量、周期分量和剩余分量,并将剩余分量视为噪声分量予以剔除;采用长短期记忆神经网络(LSTM)模型和高斯拟合(GF)算法分别进行周期分量和趋势分量的分析预测,并将二者结果进行叠加重构,得到最终预测结果。实例验证结果表明,SSA可以达到较好的数据分解和消噪效果,LSTM模型针对周期分量的预测性能优越,GF算法能够很好地实现趋势分量的拟合预测和部分信息的挖掘提取,LSTM模型和GF算法的成果重构效果良好,SSA-LSTM-GF方法具有一定的可行性和应用价值。