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.     

浅析《中图法》第四版世界地区表第四条使用规则

指出了《中图法》第四版世界地区表使用规则所存在的不足,并提出了改进方法。     

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。     

Adaptive Controller for Vehicle Active Suspension Generated Through LMS Filter Algorithms

The least means squares (LMS) adaptive filter algorithm was used in active suspension system. By adjusting the weight of adaptive filter, the minimum quadratic performance index was obtained. For two-degree-of-freedom vehicle suspension model, LMS adaptive controller was designed. The acceleration of the sprung mass,the dynamic tyre load between wheels and road,and the dynamic deflection between sprung mass and unsprung mass were determined as the evaluation targets of suspension performance. For LMS adaptive control suspension, compared with passive suspension, acceleration power spectral density of sprung mass acceleration under the road input model decreased 8-10 times in high frequency resonance band or low frequency resonance band. The simulation results show that LMS adaptive control is simple and remarkably effective. It further proves that the active control suspension system can improve both the riding comfort and handling safety in various operation conditions, and the method is fit for the active control of the suspension system.     

显露模式(Emerging Patterns)的有效挖掘

EPs可以用来在数据库中进行知识发现 ,也可以捕获时标数据库中的显露趋势或数据类之间的有用对比 .由于Apriori属性对EPs不再适用 ,而且多维数据集或小支持度阈值 (如 0 5 % )有太多的侯选项集 .对此Naive算法代价太大 ,这使得EPs的有效挖掘成为一个挑战性问题 .为解决这些问题 ,本文介绍使用精确的边界描述大型项集集合 ,设计只操作边界集的EPs挖掘算法 ,并且使用边界表示已发现的EPs .