基于遗传算法的数据预处理组合方法

进行数据挖掘之前的原始数据经常是不完整或存在异常,针对这种情况,在众多数据预处理算法的基础之上,文中提出了一种基于遗传算法的数据预处理组合方法,能有效的利用各种方法的优点,提高了估计的精确度.通过实验证明,该方法优于其他各种单一方法.     

A new variant of the Pathfinder algorithm to generate large visual science maps in cubic time

In the last few years, there is an increasing interest to generate visual representations of very large scientific domains. A methodology based on the combined use of ISI–JCR category cocitation and social networks analysis through the use of the Pathfinder algorithm has demonstrated its ability to achieve high quality, schematic visualizations for these kinds of domains. Now, the next step would be to generate these scientograms in an on-line fashion. To do so, there is a need to significantly decrease the run time of the latter pruning technique when working with category cocitation matrices of a large dimension like the ones handled in these large domains (Pathfinder has a time complexity order of O(n⁴), with n being the number of categories in the cocitation matrix, i.e., the number of nodes in the network).     

基于数据挖掘技术的专利信息分析

随着计算机技术和网络技术的的发展,各行各业积累的数据量越来越大.而专利信息集是目前世界上最大的技术信息集,几乎囊括了一切应用领域内的技术成果.为了提取隐含在其中的、人们事先不知道但又潜在有用的知识,将数据挖掘技术应用于专利信息分析,如采用聚类算法对专利文本进行挖掘、采用关联规则对专利发明人进行挖掘,以发现用户感兴趣的知识,并使之转化为有效的竞争情报.     

Apriori算法对高技能人才市场工资价位影响因素的实证分析

本文以广东为例,运用Apriori算法对广东高技能人才市场工资价位影响因素进行实证分析.研究结论认为影响高技能人才市场工资价位的主要因素与工种、地区、学历、技能、工龄、年龄有关,其中工种对收入的影响比其它都要大的多,特别是在分地区的分析中尤为明显.     

最优特征子集的遗传算法求解

指出最优特征子集选择问题(OFSS)是个NP-Hard问题,寻找一个近似算法具有现实意义。遗传算法提供了一种求解复杂系统优化问题的通用框架。使用基于小生境技术的遗传算法求解OFSS问题,以获得较好收敛性、稳定性和较快的速度。     

关于设备布局的最短路径算法模型

生产车间的设备布局设计是一个组合优化的问题。具有NP完全(Nondeterministic Polynomial Complete)、非线性等特性,常规方法较难以求解。本文提出实际路线运算法结合基因算法来求解最优设备布局结果,利用遗传算法探索生产车间设备布局问题时适值函数的确定方法。     

数据库DBF文件加解密算法与源程序

从密码学的角度叙述了数据库文件的加密、解密算法思想，分析了数据库文件．DBF的存储格式，并构造了对数据库DBF文件实现加密、解密算法和源程序。     

Digital analytics in professional work and learning

In a wide range of fields, professional practice is being transformed by the increasing influence of digital analytics: the massive volumes of big data, and software algorithms that are collecting, comparing and calculating that data to make predictions and even decisions. Researchers in a number of social sciences have been calling attention to the far-reaching and accelerating consequences of these forces, claiming that many professionals, researchers, policy-makers and the public are just beginning to realise the enormous potentials and challenges these analytics are producing. Yet, outside of particular areas of research and practice, such as learning analytics, there has been little discussion of this to date in the broader education literature. This article aims to set out some key issues particularly relevant to the understandings of professional practice, knowledge and learning posed by the linkages of big data and software code. It begins by outlining definitions, forms and examples of these analytics, their potentialities and some of the hidden impact, and then presents issues for researchers and educators. It seeks to contribute to and extend debates taking place in certain quarters to a broader professional education and work audience.     

关于数学问题的解法与计算机算法的讨论

通过实例,对数学问题在数学中的解决方法和在计算机中的算法以及算法的复杂性进行了讨论。