改进的增量式关联规则维护算法

在分析现有的关联规则算法 IUA的基础上 ,指出了该算法的不足和错误之处 ,并加以改正 ,进而提出了一种改进的增量式更新算法 EIUA. EIUA算法解决了在数据库 D不变的情况下 ,当最小支持度和最小置信度二阈值发生变化时如何高效更新关联规则的问题 .实验分析表明了新算法的有效性和优越性.     

Incremental learning of the triangular membership functions based on single-pass FCM and CHC genetic model

In order to improve the efficiency of learning the triangular membership functions (TMFs) for mining fuzzy association rule (FAR) in dynamic database,a single-pass fuzzy c means (SPFCM) algorithm is combined with the real-coded CHC genetic model to incrementally learn the TMFs.The cluster centers resulting from SPFCM are regarded as the midpoint of TMFs.The population of CHC is generated randomly according to the cluster center and constraint conditions among TMFs.Then a new population for incremental learning is composed of the excellent chromosomes stored in the first genetic process and the chromosomes generated based on the cluster center adjusted by SPFCM.The experiments on real datasets show that the number of generations converging to the solution of the proposed approach is less than that of the existing batch learning approach.The quality of TMFs generated by the approach is comparable to that of the batch learning approach.Compared with the existing incremental learning strategy,the proposed approach is superior in terms of the quality of TMFs and time cost.     

永磁同步电机的改进扩展卡尔曼滤波测速算法

针对使用增量式编码器的永磁同步电机(PMSM)伺服系统中的传统测速算法(M算法结合低通滤波)存在的时延与不准确的问题,提出了一种改进的扩展卡尔曼滤波( EKF)测速算法.该方法在不修改原有电路的前提下,利用EKF算法抑制噪声且不产生时延的特点,针对性地设计了观测模型,并通过矩阵变换与利用定点数字信号处理器累加溢出的周期...     

基于残差自然幂法的增量线性判别分析方法

提出了将增量线性判别分析问题(LDA)转化为两个增量主元分析(PCA)问题的算法框架.为加速算法的收敛速度,推导了增量LDA中训练样本的类内离散度矩阵和协方差矩阵的无损实时更新公式,并在此基础上提出了一种基于残差协方差矩阵的自然幂增量PCA算法.将该增量PCA方法与基于双PCA结构的增量LDA算法框架相结合,实现了数据...     

Novel method of mining classification information for SVM training

Support vector machine(SVM) is an important classification tool in the pattern recognition and machine learning community,but its training is a time-consuming process.To deal with this problem,we propose a novel method to mine the useful information about classification hidden in the training sample for improving the training algorithm,and every training point is assigned to a value that represents the classification information,respectively,where training points with the higher values are chosen as candidate support vectors for SVM training.The classification information value for a training point is computed based on the classification accuracy of an appropriate hyperplane for the training sample,where the hyperplane goes through the mapped target of the training point in feature space defined by a kernel function.Experimental results on various benchmark datasets show the effectiveness of our algorithm.     

基于子空间距离的局部切空间增量学习

提出一种基于子空间距离的局部切空间增量学习方法ISLTSA。首先采用基于划分的简化局部切空间排列算法SLTSA,把初始样本集划分为彼此重叠的多个局部最大线性片;然后引入向量到子空间的距离测度描述新数据点与局部最大线性片的接近程度,并将新数据点归入距离其最近的局部最大线性片中;最后,新数据点的全局低维坐标可由局部线性子空间与全局低维流形的仿射变换计算得出。对多个经典数据集的降维结果表明,ISLTSA算法能够保留数据集的局部几何性质,是一种有效的非线性增量学习方法。     

干扰受限的增量型机会中继选择协作通信

协作通信让用户以协作的方式传输信息,是下一代无线通信系统为提升频谱效率所采用的关键技术之一。实际无线通信中的期望信号除了受到信道衰落和噪声的影响外,还可能受到来自其他用户同频信号的共道干扰。随着用户数的增加,大量的共道干扰就会取代噪声成为影响无线通信质量的主要因素,称为干扰受限。提出全网总功率约束条件下的增量型解码转发机会中继选择协作通信策略,并研究该策略在Nakagami/I.I.D.Nakagami信道衰落和干扰受限环境下的协作通信性能。理论分析和仿真结果表明,该协作策略能够在Nakagami/I.I.D.Nakagami信道衰落和干扰受限环境中有效抵抗信道衰落和共道干扰,实现协作分集增益。当源节点和中继节点的功率可以灵活调整时,合理的功率分配可以进一步提升协作通信性能。     

预制拼装箱型墩抗震性能指标分析

采用IDA法对预应力预制拼装箱型高墩的抗震性能和性能指标进行研究,通过和整体式箱型高墩的表现形式对比验证了其适用性,并对墩底截面曲率、墩顶位移、预应力三个基本性能指标在预应力预制拼装箱型高墩领域的适用性进行探讨,结果表明：对于预应力预制拼装箱型高墩来说,由于高阶振型的影响,墩顶位移的大小并不能准确表征构件的损伤状态,不适合作为预应力预制拼装箱型高墩的抗震性能指标;当墩底曲率达到极限曲率时,墩底截面曲率增加幅度远大于墩身截面曲率,可以很好的反映构件的损伤状态;构件特定部位的损伤可能会导致预应力筋应力突然增大引起构件破坏,选用墩底截面曲率结合预应力指标作为性能指标能较好地表征构件的损伤状态。相关研究结论可为该类型高墩的抗震分析和设计提供借鉴。     

基于IDA和易损性分析的RC框架结构底层柱端弯矩增大系数

为研究RC框架底层柱上下端弯矩增大系数的合理取值与该系数取值的合理性,设计6栋具有不同柱端弯矩增大系数、不同设防烈度的框架结构进行增量动力分析,输入10条地震波,得到各结构模型的IDA曲线。在此基础上,通过定义不同的烈度水平,得到各结构的易损性曲线与倒塌破坏概率。结果表明:按照现行规范设计的7度设防与8度设防框架可以满足大震不倒的设防要求;若将梁柱节点与底层柱下端弯矩增大系数的取值分别提升至1.5与1.8,可使框架在特大地震作用下发生倒塌的概率降低至可接受范围之内。     

Optimal redundancy allocation for reliability systems with imperfect switching

The problem of stochastically allocating redundant com- ponents to increase the system lifetime is an important topic of reliability. An optimal redundancy allocation is proposed, which maximizes the expected lifetime of a reliability system with sub- systems consisting of components in parallel. The constraints are minimizing the total resources and the sizes of subsystems. In this system, each switching is independent with each other and works with probability p. Two optimization problems are studied by an incremental algorithm and dynamic programming technique respectively. The incremental algorithm proposed could obtain an approximate optimal solution, and the dynamic programming method could generate the optimal solution,