Research of Incremental Association Rules Mining and Applications

随着信息科学、网络技术的发展，商业活动和工程实践中的数据量以惊人的速度在膨胀，数据分析与处理所面对的数据规模也随之急剧增长。关联规则挖掘作为数据挖掘分支之一，其任务是从大量的数据中发现信息，已经成为信息产业中热门的研究课题。本文正是对数据挖掘中的增量式关联规则提取算法及应用进行研究。 Apriori算法是Agrawal提出的第一个经典关联规则挖掘算法，之后的大部分关联规则挖掘算法都是在此基础上不断地进行优化、改进，尽管这些算法各有优点，但在实际应用中都面临着这样两个问题：一是当数据频繁地增加或更新时，如何进行增量式规则提取？如果对于增加少量数据后的数据集重新运行一次算法，势必会造成效率的下降...As the Information Science and Network Technology develops, the data sets from business activities and engineering practice are expanding rapidly, data analysis and processing face large and large data scale. As an important subdomain of data mining, Association rules mining is to find hidden information from the data set, and it has caused more and more attention for its significance in theory an...学位：工学硕士院系专业：软件学院_计算机软件与理论学号：2432007115184

Incremental association rules mining for large data set

商业活动和工程实践中通常会积累一些大规模的携带重要信息的数据,由于这种数据集经常有更新且数据量较大,在对它们进行增量式关联规则挖掘时,若采用基于传统的APrIOrI算法进行计算,一方面难以取得较好的效率;另一方面支持度设置过低会产生大量的冗余规则,设置过高则会把一些支持度不高但有用的规则过滤掉而导致算法对这些新规则感应迟钝。因此,借助遗传算法的相关机理,同时结合自然界的免疫进化理论及相关仿生机制,提出一种IOgA(IMMunE OPTIMIzATIOn bASEd gEnETIC Al-gOrITHM,基于免疫优化的遗传算法)增量式关联规则挖掘方法。通过实验表明,该方法应用于大规模数据集的增量式关联规则挖掘时,可以及时地感知规则的变更并发现有用的规则,减少了冗余规则的产生,同时挖掘效率也有明显提高。Business activity and engineering practice always accumulate large dataset with important information.But because of the dataset's largeness and frequent updating,if the Apriori based algorithm is applied to incremental association rules mining,it is not only inefficient,but also many redundant rules will be produced with low minimum support while some interesting rules will be lost with high minimum support,which leads to the algorithm's blunt perception to those rules.So,following genetic principle,and com-bining with natural immune involution theory and relative bionic mechanism,this paper proposes an IOGA(Immune Optimization based Genetic Algorithm)approach for incremental association rules mining.Experiment demonstrates the proposed method's effective-ness and presents its good performance in perceiving rules'subtle change,reducing redundant rules and finding interesting rules

Loop-Mediated Isothermal Amplification(LAMP) for Detection of Alicyclobacillus acidoterrestris in Foods

目的:利用环介导等温扩增技术建立食品中酸土环脂芽孢杆菌快速检测方法。方法:针对酸土环脂芽孢杆菌16S序列设计特异引物,再优选反应体系,用显色法检测实验结果。结果:该方法能够在63℃条件下1 H内检出食品中酸土环脂芽孢杆菌,所设计的引物有良好的特异性;灵敏度达6.7 Cfu/M l(弱阳性)。结论:该方法具有高效、特异性强和敏感性高等特点,可满足酸土环脂芽孢杆菌快速检测筛选的要求。Purpose: A loop-mediated isothermal amplification(LAMP) method was established for the detection of Alicyclobacillus acidoterrestris in foods.Methods: After optimization of the reaction conditions of LAMP including the concentrations of primers, reaction time and amplification temperature, the LAMP method was developed, and its sensitivity and specificity were evaluated.Results: The method was capable of rapidly and specifically detecting A.acidoterrestris in foods within 1 hour at a constant temperature of 63 ℃.The sensitivity of the method was 6.7 CFU/m L and the specificity was 100%.Conclusions: The LAMP method is efficient, highly sensitive and specific, and suitable for the rapid detection of A.acidoterrestris in various food samples.福建省漳州市自然科学基金项目(ZZ2012J16

洱海近50a来沉水植被演替及其主要驱动要素

依据文献报道的洱海水质、水文（水位）和沉水植被（物种组成、生物量及分布面积）数据,分析了近50年来洱海的水质变化、水位波动情况以及沉水植被的演替过程,探讨了驱动洱海沉水植被演替的主要环境因子.分析表明,洱海沉水植被群落经历了原生、过渡、顶级和衰退等主要阶段;自1980s以来,流域入湖营养盐增加、水质持续下降、藻类生物量逐年升高、沉水植被群落结构简单化和抑藻功能退化等因素是驱动洱海沉水植被演替与分布的原动力,水位大幅波动加速了洱海水生态系统由清水态向浊水态转变,并导致沉水植物大量衰退和某些特有物种消失.因此,在洱海水生态系统的治理以及沉水植被的恢复过程中,应优先考虑降低外源营养盐输入和优化水位调控