基于单元输入输出模型控制系统故障树自动建造的一种方法

在已有控制系统故障树的自动建造方法的基础上,提出一种基于单元输入输出模型的自动建树方法．通过对系统组成单元的故障模型和输入输出变量间偏差的传输增益分析,建立单元输入输出模型,并建立了相应的数据库,对数据库搜索建立故障树．给出了一种自动识别控制环的算法．本文给出的故障树建造方法,不仅能较好地解决复杂控制系统的建树的开放性和可移植性,而且自动化程度较高．     

对称群上基于极小对换生成集的Cayley图的同构

Sn为n阶对称群,A,B是Sn的两个极小生成集,且其中的元素都为对换,Tra(A),Tra(B)则分别是A,B的对换树.Cay(Sn,A),Cay(Sn,B)分别表示群Sn关于A,B的Cayley图,证明了:Cay(Sn,A)■Cay(Sn,B)Tra(A)■Tra(B).同时也说明,同阶对称群上不同构的两Cayley图可能会有很相似的性质,如都是点传递图,自同构群相同,圈结构也相同.     

一种改进的区间值属性决策树学习算法

通过引进新的非平稳割点定义,提出了改进的区间值属性决策树学习算法,改进后学习算法的效率有很大程度的提高。     

广东省古树名木普查分析

根据此次调查：广东省目前有古树名木共有23179株(群)．其中一级古树693株,占3．0％;二级古树2387株,占10．3％;三级古树19964株,占86．1％;名木135株,占0．6％．按地域分：在城市生长的有3239株,占总株数的14．0％;生长在农村的有19940株,占86．0％．按生长环境分：生长在单位庭院的有1574株,占6．8％;个人宅院的有631株,占2．7％;寺院的521株,占2．2％．其它的有20453株,占88．3％．广东省古树名木共有珍稀濒危植物24种,其中渐危种14种、濒危种1种、稀有种9种。     

生物技术在果树学研究中的应用

主要对微繁殖、单倍体、胚培养、原生质体培养与体细胞杂交、基因转化及分子标记等技术在果树学研究中的应用进行了综述.     

植物转基因研究进展

本文主要对农作物和苹果、葡萄、柑橘、番木瓜、猕猴桃、香蕉、草莓等果树转基因研究进展进行了综合评述．     

通过平面上几个定点的最短路

本文定义了平面上ｎ个点的附加节点和最短路．讨论了附加节点与最短路之间的关系，找出了 附加节点的选择方法，然后给出最短路，采用减少点数的方法，先确定三个点的最短路，然后给出 ｎ个点的最短路．（ｎ≥３）．     

Unclassed matrix shading and optimal ordering in hierarchical cluster analysis

A method is presented for the graphic display of proximity matrices as a complement to the common data analysis techniques of hierarchical clustering. The procedure involves the use of computer generated shaded matrices based on unclassed choropleth mapping in conjunction with a strategy for matrix reorganization. The latter incorporates a combination of techniques for seriation and the ordering of binary trees.Partial support for this research was provided by NIJ Grant #82-IJ-CX-0019 and NSF Grant #SES82-06067. The authors wish to acknowledge the assistance of Professors L.J. Hubert, R.G. Golledge, and W.R. Tobler.     

Piecewise hierarchical clustering

We consider two or more ultrametric distance matrices defined over different, possibly overlapping, subsets. These matrices are merged into one ultrametric matrix defined over the whole set. Necessary and sufficient conditions for uniqueness of the merging are established. when these conditions are not satisfied, consistent algorithms are given.The author thanks B. Monjardet and two anonymous referees for their helpful comments.     

N-trees as nestings: Complexity,similarity, and consensus

Interpreting a taxonomic tree as a set of objects leads to natural measures of complexity and similarity, and sets natural lower bounds on a consensus tree Interpretations differing as to the kind of objects constituting a tree lead to different measures and consensus Subset nesting is preferred over the clusters (strict consensus) and even the triads interpretations because of its superior expression of shared structure Algorithms for computing the complexity and similarity of trees, as well as a consensus index onto [0,1], are presented for this interpretation The full consensus is defined as the only tree which includes all the nestings shared in a profile of rival trees and whose clusters reflect only nestings shared in the profile The full consensus is proved to exist uniquely for each profile, and to equal the Adams consensusThe author is grateful for the many helpful comments on presentation from Frances McA Adams, William H E Day, and Christopher A Meacham