Study on the Application of Association Rules in Temporal Data Mining

20世纪80年代末，数据挖掘作为一个全新的研究领域悄然出现并迅速发展。数据挖掘的研究目的是在大型数据集中发现那些隐藏的、人们感兴趣的具有特定规律的信息。作为数据挖掘对象之一的时态数据库是由随时间变化的一系列序列值或事件组成的数据库。时态数据挖掘的研究对商业、金融、医疗诊断、科学与工程等领域的数据分析具有重要意义，因而时态数据的挖掘方法也成为数据挖掘的一个研究热点。 关联规则一直是近年来数据挖掘和人工智能领域研究的热点课题，目前在客户关系管理、医学、生物等领域已有应用。传统的关联规则挖掘过程通常不考虑时间约束，如购物篮分析等。由于时态数据库规模不断壮大，重要性不断加强，如何将关联规则挖掘应用到...In the later 1980’s, Data Mining-a new research field, appears gradually and develops rapidly. The study purpose of Data Mining is to find the regular information which hided in large data set and people interested in. As one of the mining objects of Data Mining, temporal data base is composed by series of sequence or affair. The study of temporal data mining plays an important role in the data an...学位：经济学硕士院系专业：经济学院计划统计系_经济信息管理学学号：2005130077

Construction of Weighted Temporal Association Rules in Data Mining

传统的关联规则很少考虑规则的时间适用性,而时态关联规则中每条关联规则都有其成立的时间区域,对上述问题进行了一定的改进。该文在此基础上,构造了一种体现数据时间价值的加权时态关联规则,以使规则的发现体现一种时间趋势,并对同一组数据采用不同关联规则挖掘的结果进行比较,取得了良好的效果。The fitness of time is seldom illustrated by traditional association rules. Temporal association rules are improved by regarding every association rule with valid time area. Weighted temporal association rule is presented in this paper based on these researches, which can reflect the time value of data and the time tendency of discovered rules, and the results of different association rules mining on the same data are also compared and achieve a fine performance.国家教育部新世纪优秀人才计划基金资助项目(NCET-04-0608);; 国家教育部社科研究规划基金资助项目(06JA910003

An Analysis of Natural Resources in China by Revised Solow Model

改革开放以来,中国经济取得了举世瞩目的成就,在这些成就的背后也存在一些无法忽视的问题。针对制约中国经济增长的能源问题,依据索洛经济增长理论中环境与经济增长部分的理论依据,采用石油这一主要能源,并对索洛模型进行了一些修正,据此分析了自然资源对中国经济增长的限制性影响。结果表明:能源的日益紧缺会给经济增长带来负面影响,解决能源短缺问题已迫在眉睫。Some problems that are unable to ignore have existed along with the great achievements in Chinese economic construction.Aiming at the restriction of natural resources to the economic growth of China,this paper uses petroleum and the expands Solow Model to analyze the problem on the basis of the environment and the economic growth theory,with the conclusion that the decreasing natural resources will restrict the economic growth to a certain extent,and the problem is in dire need of solution

Functional Data Mining: Application in the Analysis of Chinese Consumption Function

以数据挖掘的思想,提出了利用Bernstein基构建一般函数数据的方法。在此基础上,根据中国31个省(自治区、直辖市)城镇居民的人均年收入和消费性支出的数据,构建了消费函数数据,并进行误差分析,求出消费函数的一阶和二阶导数,进一步挖掘消费函数的发展速率,取得良好的效果。Based on the idea of data mining,a method of using Bernstein bases to construct general functional data is given in this article.With the data of urban per capita annual income and consumptive expenditure in 31 provinces(Autonomous regions,Municipalities) of China,consumption functional data is constructed and error analysis is done based on this study.In order to further mining the developing velocity of consumption function,first and second order derivatives of the function are computed and good effect achieved.教育部“新世纪优秀人才支持计划项目”《数据挖掘中最新统计方法研究》(NCET-04-0608);; 教育部社科研究规划项目《数据挖掘中关联规则的统计研究及应用》(06JA91003

JUNO Sensitivity on Proton Decay p→νˉK+p\to \bar\nu K^+ Searches

The Jiangmen Underground Neutrino Observatory (JUNO) is a large liquid scintillator detector designed to explore many topics in fundamental physics. In this paper, the potential on searching for proton decay in $p\to \bar\nu K^+$ mode with JUNO is investigated.The kaon and its decay particles feature a clear three-fold coincidence signature that results in a high efficiency for identification. Moreover, the excellent energy resolution of JUNO permits to suppress the sizable background caused by other delayed signals. Based on these advantages, the detection efficiency for the proton decay via $p\to \bar\nu K^+$ is 36.9% with a background level of 0.2 events after 10 years of data taking. The estimated sensitivity based on 200 kton-years exposure is $9.6 \times 10^{33}$ years, competitive with the current best limits on the proton lifetime in this channel