射流原理在微粉粒度分级中的应用

本文阐述平面射流附壁流动原理——Coanda效应,以及它被应用于微粉粒度分级操作的试验结果。分级的颗粒范围小于10μm。     

关于中国古代文学史编写的几点思考

我国文学史的编写存在不少问题：一是在文学理念、缟写模式和文体分类上受西方影响太大，而顾度中国文学的实际不够；二是客观叙述不够，议论、阐释、评析太多，未尽可能地还原中国文学的历史面貌；三是在元、明、清文学的璃排上反映出明显的重小说、戏曲，轻诗、文、词、赋的倾向，背离了元、明、清文学仍以诗文为主体的基本事实。     

The generation of random,binary unordered trees

Several techniques are given for the uniform generation of trees for use in Monte Carlo studies of clustering and tree representations. First, general strategies are reviewed for random selection from a set of combinatorial objects with special emphasis on two that use random mapping operations. Theorems are given on how the number of such objects in the set (e.g., whether the number is prime) affects which strategies can be used. Based on these results, methods are presented for the random generation of six types of binary unordered trees. Three types of labeling and both rooted and unrooted forms are considered. Presentation of each method includes the theory of the method, the generation algorithm, an analysis of its computational complexity and comments on the distribution of trees over which it samples. Formal proofs and detailed algorithms are in appendices.     

Averaging over decision trees

Pruning a decision tree is considered by some researchers to be the most important part of tree building in noisy domains. While there are many approaches to pruning, the alternative of averaging over decision trees has not received as much attention. The basic idea of tree averaging is to produce a weighted sum of decisions. We consider the set of trees used for the averaging process, and how weights should be assigned to each tree in this set. We define the concept of afanned set for a tree, and examine how the Minimum Message Length paradigm of learning may be used to average over decision trees. We perform an empirical evaluation of two averaging approaches, and a Minimum Message Length approach.This work has been carried out with the support of the Defence Research Agency, Malvern.     

区域产业评价与分类方法及应用

区域主导产业评价与选择是产业结构调整的核心。根据洞庭湖区的特点,提出了区域产业评价的指标体系,利用层次分析法确定准则权重,利用ELECTRE TRI法对区域产业进行分类,进而确定主导产业。通过对某县的产业进行分类和对主导产业进行确定,说明该方法的可行性和有效性。     

《中国图书馆分类法》第5版“中国地区表”的修订与使用

介绍了《中国图书馆分类法》(第5版)"中国地区表"的修订情况,对分类标引时应注意的问题进行了阐述,并举例说明。     

基于DCT域特征和Bayes语义分类的教学图像资源库检索技术

提出了一种根据DCT域特征提取和Bayes语义分类结合的图像检索技术。针对图像库数据结构的语义需求,采用朴素Bayes算法对图像库进行分类;其中视觉特征提取部分,采用改进的DCT域的边缘空间分布概率特征提取方法,获取目标对象边缘信息,建立20个特征值;通过Bayes分类器的分类,获取每类的索引特征向量,用于初次语义类别过滤,提高了检索效率。通过实验,建立教学需要的图像资源库,与其它检索算法进行查准率对比试验,证明了本算法的优越性。     

面向对象的继承机制

本文对面向对象的继承机制从继承的种类、继承的内容、继承的作用等几个方面进行了探讨。     

C&RT决策树在民办高校招生中的应用分析

以往的数据挖掘技术的应用大多是在金融领域,而在其他领域里面应用不是很多,如在高校招生中的应用更是如此。在数据挖掘中,决策树提供了一种展示类似在什么条件下会得到什么值这类规则的方法,是用二叉树形图来表示处理逻辑的一种技术。特别适合于判断因素比较少、逻辑组合关系不复杂的情况。它可以直观、清晰地表达加工的逻辑要求,满足用户需求,为管理决策者提供相应的决策支持。以某高校招生数据作为基础信息为依据,对高校招生中生源地与报到情况等进行CART(Classification and Regression Tree)分析,将对决策树分析的应用做进一步的阐述。     

支持向量机的凸优化求解

支持向量机(SVM)是一种基于统计学习理论的机器学习方法,由于其优越的学习性能,已经成为当前模式识别、数据挖掘、大数据处理等机器学习领域的研究热点.查阅相关同类文章,发现其中对SVM理论中公式,如距离函数d、拉格朗日函数L(w,b,α)、二次凸优化函数f(x)等的来龙去脉缺少细致的阐述.本文对SVM理论中典型的线性最优二分类问题的求解进行了完整的推导,并给出了对岩屑岩性分类识别的结果,也为今后的非线性多类模式分解作出铺垫.