关于一类自相似集的上密度

研究了自相似集上的Hausdorff测度H的上s密度,尤其对于E是一个自相似集,且满足条件c^1＋1-3c＋1=0,l∈N,c是相似集E上的比例常数,获得了一类自相似集E上的Hausdorff测度的精确上s密度．     

基于离散量算法预测酶的亚类

从酶的一级序列出发,以20种氨基酸和其紧邻与次邻的氨基酸二联体在序列中出现的个数为参数,用离散量算法对酶的亚类进行预测.通过用Self-consistency和Jack-knife两种检验方法检验时,均获得较好的预测精度.结果表明该方法新颖、简单、有效.     

一种基于软件的数据时标修正算法

测控领域中,系统对测角数据时标的格式有很高的要求。针对该领域内测角数据出现的时标异常问题,提出了一种基于软件,对异常数据时标进行实时修正的算法。在保证数据有效性的同时,实现了对测角数据时标的纠错。     

Multiple-Instance Learning with Instance Selection via Constructive Covering Algorithm

Multiple-Instance Learning （MIL） is used to predict the unlabeled bags＇ label by learning the labeled positive training bags and negative training bags.Each bag is made up of several unlabeled instances.A bag is labeled positive if at least one of its instances is positive,otherwise negative.Existing multiple-instance learning methods with instance selection ignore the representative degree of the selected instances.For example,if an instance has many similar instances with the same label around it,the instance should be more representative than others.Based on this idea,in this paper,a multiple-instance learning with instance selection via constructive covering algorithm （MilCa） is proposed.In MilCa,we firstly use maximal Hausdorff to select some initial positive instances from positive bags,then use a Constructive Covering Algorithm （CCA） to restructure the structure of the original instances of negative bags.Then an inverse testing process is employed to exclude the false positive instances from positive bags and to select the high representative degree instances ordered by the number of covered instances from training bags.Finally,a similarity measure function is used to convert the training bag into a single sample and CCA is again used to classification for the converted samples.Experimental results on synthetic data and standard benchmark datasets demonstrate that MilCa can decrease the number of the selected instances and it is competitive with the state-of-the-art MIL algorithms.     

基于距离的区间值Vague集的多准则决策方法

研究将实数型Vague集的距离方法扩展成为区间值Vague集的距离度量方法. 给出区间值Vague集的模糊度定义和Hausdorff距离,建立基于距离的区间值Vague集多准则决策的相对优属度法,并通过例子说明实施方法的步骤.     

独立式窑洞地震作用下损伤指标研究

定量地评估结构在地震作用下的损伤是地震工程领域的研究重点,增量动力分析方法已被广泛用于建筑结构地震易损性评估,而结构损伤指标是定量评估结构损伤情况的重要参数,山西北部农村地区的独立式土坯窑洞是一种拱受力结构体系,为研究拱结构在地震作用下的破坏特征并确立结构损伤指标,结合实际震害与数值模拟试验,分析了窑洞结构在地震作用下的破坏特征,对比了窑洞结构的顶点水平位移和拱顶竖向位移在不同地震动峰值加速度下与结构损伤情况对应关系,发现窑洞拱顶竖向位移与窑洞拱矢高作为窑洞损伤指标较为合理。