基于层面信息的路径优化

根据分层物体快速成型（LOM）中零件逐层累积的特点，从缩短加工时间、提高制件效率方面着手阐述了路径优化的必要性，针对LOM机的运动机理和软件数据结构，给出了扫描路径优化的原理，将图论中的便宜算法用于LOM机的扫描路径优化。     

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．     

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。     

Seismic 3D Prestack Time Migration on Parallel Computers

Ｓｅｉｓｍｉｃ３ＤＰｒｅｓｔａｃｋＴｉｍｅＭｉｇｒａｔｉｏｎｏｎＰａｒａｌｌｅｌＣｏｍｐｕｔｅｒｓ￥ＬｉｕＰｉｎｇ＆ＣｈｅｎＹｕｎｈｅ（ＷｕｈａｎＤｉｇｉｔａｌＥｎｇｉｎｅｅｒｉｎｇｉｎｓｔｉｔｕｔｅ，ＷｕｃｈａｎｇＰ．Ｏ．Ｂｏｘ７４２２３，Ｐ．Ｒ．...     

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。     

Using genetically-defined rodent strains for the identification of hippocampal traits relevant for two-way avoidance behavior: a non-invasive approach

Summary Genetically-defined rodent strains permit the identification of hippocampal traits which are of functional relevance for the performance of two-way avoidance behavior. This is exemplified here by analyzing the relationship between infrapyramidal mossy fibers (a tiny projection terminating upon the basal dendrites of hippocampal pyramidal neurons) and two-way avoidance learning in about 800 animals. The necessary steps include 1) identification of structural traits sensitive to selective breeding for extremes in two-way avoidance, 2) testing the robustness of the associations found by studying individual and genetical correlations between hippocampal traits and behavior, 3) establishing causal relationships by Mendelian crossing of strains with extreme structural traits and studying the behavioral consequences of such structural randomization, 4) confirming causal relationships by manipulating the structural variable in inbred (isogenic) strains, thereby eliminating the possibility of genetic linkage, and 5) ruling out the possibility of spurious associations by studying the correlations between the hippocampal trait and other behaviors known to depend on hippocampal functioning.In comparison with the classical lesion approach for identifying relationships between brain and behavior, the present procedure appears to be superior in two aspects: it is non-invasive, and it focuses automatically on those brain traits which are used by natural selection to shape behaviorally-defined animal populations, i.e., it reveals the natural regulators of behavior.     

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.     

两地点8年生柏木生长性状家系变异及选择

【目的】揭示柏木生长性状的遗传变异规律,为高阶遗传改良筛选优良种质,选择优良家系,及其区域推广奠定基础。【方法】以营建在浙江省开化县林场(KH)和湖北省太子山林场(TZS)两个试验点的8年生柏木优树子代家系为材料,分析其生长性状的遗传变异,估算其育种值、遗传力等参数。【结果】柏木生长性状(树高、胸径和材积)的遗传变异系数为3.08%～13.93%,其中材积的变异最大。子代家系的树高、胸径和材积在地点间差异显著,TZS点的单株材积高于KH点315.79%,且家系与地点间的交互效应显著。胸径、树高和材积具有显著的家系效应,KH和TZS试验点的家系遗传力变幅分别为0.42～0.61和0.58～0.74。KH和TZS试验点分别以单株材积育种值大于CK的10%和45%为标准,各选出6个优良家系,现实增益分别为33.51%和67.95%。利用独立淘汰法,在KH点和TZS点各筛选优良单株17和12株,材积的遗传增益分别为41.38%和40.92%。【结论】8年生柏木优树子代家系生长性状具有较大的遗传改良潜力,但家系与环境的互作效应显著;通过子代家系的遗传评价有助于种子园建园亲本的再选择和现有种子园的...     

应用禁忌粒子群算法的车间调度及其并行化实现

为了解决批量生产、制造、装配等车间调度问题,基于Hadoop集群,提出应用禁忌粒子群算法的车间调度及其并行化实现.以某装载机制造车间最小化完成时间为目标,通过使用禁忌粒子群算法对车间调度问题进行求解.结果表明：在车间批量大的情况下,禁忌粒子群算法可得出有效的调度方案,避免算法陷入局部最优解.与现有的智能算法相比,禁忌粒子群算法更有利于实现全局最优解.     

基于量子微粒群优化算法的半透明介质光学参数反演

针对半透明介质光学参数估计问题,建立了脉冲激光辐照下半透明介质光学参数反演模型,采用量子微粒群优化(QPSO)算法反演了折射率和吸收系数,分析了测量误差、热物性参数对反演结果的影响,并利用敏感性分析揭示了反演精度与测量误差的关系.计算结果表明：建立的反演模型和采用的QPSO算法可以精确估计折射率和吸收系数,即使人为添加10%的测量误差,反演结果依然具有较强的鲁棒性和准确度.本研究可为半透明介质物性参数获取提供技术参考.