一种基于投影数据库的SPAM算法

序列模式挖掘是数据挖掘的重要分支,关于序列模式挖掘的算法非常多,SPAM算法就是序列模式挖掘算法的一种,Perfixspan算法(基于投影的算法)也是序列模式挖掘算法的一种。SPAM算法和Perfixspan算法各有优缺点。研究这两种算法的基础上给出了一种结合这二种算法优点进行改进的算法。     

引入相关反馈的基于内容音频检索研究

提出两种基于内容的音频检索的相关反馈算法,一种算法是在对正反馈图像检索技术的改进基础上提出的;另一种算法的提出是基于强制优化概念思想.实验表明,后一种算法比前一种算法具有更好的性能,并且它以一种统一的机制,充分利用了负反馈和正反馈的特性.     

模糊决策树算法与清晰决策树算法的比较研究

ID3算法是一种典型的决策树归纳算法,这种算法在假定示例的属性值和分类值是确定的前提下,使用信息熵作为启发式建立一棵清晰的决策树。针对现实世界中存在的不确定性,人们提出了另一种决策树归纳算法,即模糊决策树算法,它是清晰决策树算法的一种推广。这两种算法在实际应用中各有自己的优劣之处,针对一个具体问题的知识获取过程,选取哪一种算法目前还没有一个较明确的依据。该文从5个方面对这两种算法进行了详细的比较,指出了属性为连续值时这两种算法的异同及优缺点,其目的是在为解决具体问题时怎样选择这两种算法提供一些有用的线索。     

二值分解压缩和Consensus算法

奇异值分解(SVD)是一种流行的用于高维数据压缩的方法,二值分解是奇异值分解的一种简化形式.实现二值分解的主要算法有两种:迭代启发式算法和贪婪算法.但这两种算法都不是很理想的算法:迭代启发式算法在很多情况下不能保证收敛性,贪婪算法不满足大型数值矩阵分解的需要.采用了一种新的算法来实现二值分解:Consensus的算法.Consensus算法可在渐进多项式时间内找到一般图中的极大二分团.对于某些二分图,该算法的复杂度是多项式时间的.实验结果表明,当迭代启发式算法不起作用时,Consensus算法是一种很好的求解二值分解的方法.该算法远比贪婪算法的效率高,且具有稳定收敛性.     

一种基于粒子群优化算法和差分进化算法的新型混合全局优化算法

提出一种基于粒子群算法(PSO)和差分进化算法(DE)相结合的新型混合全局优化算法——PSODE．该算法基于一种双种群进化策略，一个种群中的个体由粒子群算法进化而来，另一种群的个体由差分操作进化而来．此外，通过采用一种信息分享机制，在算法执行过程中两个种群中的个体可以实现协同进化．为了进一步提高PSODE算法的性能，摆脱陷入局部最优点，还采用了一种变异机制．通过4个标准测试函数的测试并与PSO和DE算法进行比较，证明本文提出的PSODE算法是一种收敛速度快、求解精度高、鲁棒性较强的全局优化算法．     

改进型蚁群算法的多处理机任务调度研究

蚁群算法是一种新型的模拟进化算法,具有正反馈、分布式计算等特点,是一种解决组合优化问题的有效算法。在介绍蚁群算法基本原理以及探讨该算法的缺陷基础上,针对多处理器任务调度问题,提出了一种基于改进型蚁群算法的调度策略。仿真研究表明,该算法具有优良的全局优化性能,效果令人满意。     

Bagging算法在中文文本分类中的应用

Bagging算法是目前一种流行的集成学习算法,采用一种改进的Bagging算法Attribute Bagging作为分类算法,通过属性重取样获取多个训练集,以kNN为弱分类器设计一种中文文本分类器。实验结果表明Attribute Bagging算法较Bagging算法有更好的分类精度。     

数据挖掘中决策树加权模糊熵算法

决策树算法是数据挖掘技术领域的一种重要算法 ,唐华松、姚耀文在利用熵和加权和思想的基础上提出了一种加权熵算法 ,但是此算法在解决模糊问题上有其不足之处 ,我们在加权熵算法的基础上利用模糊理论建立了一种加权模糊熵算法 ,较好的解决了这一问题。     

一种有效的聚类分析算法的研究

本文在综合分析层次凝聚算法和k平均分区算法的优缺点和借鉴前人算法的基础上,提出了一种改进算法(ICAA算法)。实验证明ICAA算法是一种速度更快、效率更高、聚类质量更好的算法。     

一种轻量级动态密钥建立算法研究

解决射频识别（RFID）和低运算能力设备安全的理想方法就是实现一种动态密钥建立算法,但是经典的动态密钥建立算法都不适用于RFID。旨在研究一种为RFID标签和低运算能力设备提供动态密钥建立的算法。基于TPM的密钥建立算法为轻量级的动态密钥建立提供了方法,KKK算法就是其中一种算法。研究了KKK算法的原理以及KKK算法的发展现状,建立了KKK算法仿真环境,并且实现了已经提出的大部分KKK类算法;提出了一种具有更强攻击效果的攻击算法——改进的遗传攻击算法,实验结果表明该算法优于目前提出的其他攻击算法。     

混合关系中的函数依赖及其相关规则

在实际应用中有这样一类关系数据库,其中数据项在某个属性上的取值本身又是一个关系。讨论这种混合关系中的函数依赖及其相应的相关规则具有一定的理论意义和实际应用价值。给出这种混合关系的形式定义、混合关系中4种类型的函数依赖关系以及相应的4种类型的相关规则;并给出混合关系到一般关系的转换,通过这个转换说明了混合关系与普通关系的联系及其差别。给出一个实际应用中的例子,来说明混合关系中的函数依赖和相关规则的形式多样性。     

Generalized theory of uncertainty (GTU)—principal concepts and ideas

Uncertainty is an attribute of information. The path-breaking work of Shannon has led to a universal acceptance of the thesis that information is statistical in nature. Concomitantly, existing theories of uncertainty are based on probability theory. The generalized theory of uncertainty (GTU) departs from existing theories in essential ways. First, the thesis that information is statistical in nature is replaced by a much more general thesis that information is a generalized constraint, with statistical uncertainty being a special, albeit important case. Equating information to a generalized constraint is the fundamental thesis of GTU. Second, bivalence is abandoned throughout GTU, and the foundation of GTU is shifted from bivalent logic to fuzzy logic. As a consequence, in GTU everything is or is allowed to be a matter of degree or, equivalently, fuzzy. Concomitantly, all variables are, or are allowed to be granular, with a granule being a clump of values drawn together by a generalized constraint. And third, one of the principal objectives of GTU is achievement of NL-capability, that is, the capability to operate on information described in natural language. NL-capability has high importance because much of human knowledge, including knowledge about probabilities, is described in natural language. NL-capability is the focus of attention in the present paper. The centerpiece of GTU is the concept of a generalized constraint. The concept of a generalized constraint is motivated by the fact that most real-world constraints are elastic rather than rigid, and have a complex structure even when simple in appearance. The paper concludes with examples of computation with uncertain information described in natural language.     

基于反步法的移动机器人鲁棒跟踪控制

以四轮移动机器人为研究对象,建立了机器人完整的数学模型,包括运动学模型、动力学模型以及驱动电机模型。在机器人数学模型的基础上,采用反步法的思想设计具有全局收敛特性的鲁棒轨迹跟踪控制器,设计中考虑了驱动电机模型使控制器更符合实际控制要求,并将其分解为运动学控制器、动力学控制器以及电机控制器三部分,降低了控制器设计的难度。构造了系统的李雅普诺夫函数,证明了该类型移动机器人在所得控制器作用下,能实现对给定轨迹的全局渐近追踪。仿真实验结果表明基于反步法的控制器是有效的。     

K(Knowledge)-net: building up and its dynamics

The essence of intelligence is to use certain abilities to obtain knowledge, to use that knowledge, and to operate with that knowledge. New knowledge learned by a human is often related to old existing knowledge, and sometimes we could have more conceptual knowledge based on old knowledge. So, the knowledge in the brain exists in a related structural form, and this structure is dynamic, and therefore is evolvable. Based on the understanding of the real process of learning by a human being, we discuss how to make a model to describe the dynamic structure of knowledge. This model is also a principle of artificial brain design. Most of the knowledge a child learns is from natural language and perception information, and we define this as semantic knowledge. The model to describe the process and structure of knowledge growing in a network form is called a K-net. It is a dynamic network with two main dynamics: one is new knowledge added, and the other is aggregating knowledge existing in the network with some probability. Under these very natural conditions, we found that the network is originally a simple random net, and then some characteristics of a complex network gradually appear when more new knowledge is added and aggregated. A more interesting phenomenon is the appearance of a random hierarchical structure. Does this mean emergence?     

Fault tolerant control for joint structure in PEMS high speed maglev train

The PEMS high speed maglev train, which features a permanent magnet inside an electromagnet, is a new kind of maglev train for long distance intercity transportation. The joint structure, which consists of two single levitation sub‐systems, is the fundamental levitation unit. Two kinds of faults are considered and corresponding fault tolerant control strategies are proposed. The first fault condition is when a gap sensor that is part of a single levitation system is faulty. For this kind of fault, a fault tolerant control strategy based on signal reconfiguration is proposed. The second fault condition is when the whole of a single levitation sub‐system is faulty. Under this condition, a faulty model is firstly established, then a fault tolerant control strategy is designed. When this kind of fault is detected, a switch from the normal controller to the fault tolerant controller can make the faulty system stable.     

Using genetic algorithm for lot sizing and scheduling problem with arbitrary job volumes and distinct job due date considerations

This paper considers an integrated lot sizing and scheduling problem for a production–distribution environment with arbitrary job volumes and distinct due dates considerations. In the problem, jobs are firstly batch processed on a batching machine at production stage and then delivered to a pre-specified customer at the subsequent delivery stage by a capacitated vehicle. Each job is associated with a distinct due date and a distinct volume, and has to be delivered to the customer before its due date, i.e. delay is not allowed. The processing time of a batch is a constant independent of the jobs it contains. In production, a constant set-up time as well as a constant set-up cost is required before the first job of this batch is processed. In delivery, a constant delivery time as well as a constant delivery cost is needed for each round-trip delivery between the factory and the customer. Moreover, it is supposed that a job that arrives at the customer before its due date will incur a customer inventory cost. The objective is to find a coordinated lot sizing and scheduling scheme such that the total cost is minimised while guaranteeing a certain customer service level. A mixed integer formulation is proposed for this problem, and then a genetic algorithm is developed to solve it. To evaluate the performance of the proposed genetic algorithm, a lower bound on the objective value is established. Computational experiments show that the proposed genetic algorithm performs well on randomly generated problem instances.     

Distributed speculative execution for reliability and fault tolerance: an operational semantics

This paper examines the use of speculations, a form of distributed transactions, for improving the reliability and fault tolerance of distributed systems. A speculation is defined as a computation that is based on an assumption that is not validated before the computation is started. If the assumption is later found to be false, the computation is aborted and the state of the program is rolled back; if the assumption is found to be true, the results of the computation are committed. The primary difference between a speculation and a transaction is that a speculation is not isolated—for example, a speculative computation may send and receive messages, and it may modify shared objects. As a result, processes that share those objects may be absorbed into a speculation. We present a syntax, and an operational semantics in two forms. The first one is a speculative model, which takes full advantage of the speculative features. The second one is a nonspeculative, nondeterministic model, where aborts are treated as failures. We prove the equivalence of the two models, demonstrating that speculative execution is equivalent to failure-free computation.     

Dynamic anti-windup based control method for state constrained systems

Based on the dynamic anti-windup strategy, an alternative control methodology for state constrained systems is presented. The proposed method is an a posteriori approach for state constrained systems, which is differentiated from the usual a priori approach. That is, first a linear controller is designed to show a desirable nominal performance by ignoring state constraints. Then, an additional compensator is introduced to account for state constraints. By minimizing a reasonable performance index, a dynamic compensator is derived explicitly, which is expressed in plant and controller parameters. The proposed method not only provides a graceful performance degradation, but it also guarantees the total stability of the resulting systems. An illustrative example is given to show the effectiveness of the proposed method.     

赋权图匹配问题的一种新的松弛模型

图匹配是一个NP难(NP-hard)问题. 基于置换矩阵是非负正交矩阵这一经典结论, 提出赋权图匹配(Weighted graph matching, WGM)的双向松弛障碍规划, 理论上证明新模型的解与原模型的解是一致的. 该规划是一个二元连续规划, 它是正交矩阵上的线性优化问题, 同时也是非负矩阵上的凸二次优化问题. 故设计求解新模型的交替迭代算法, 并证明算法的局部收敛性. 数值实验表明, 在匹配精度方面, 新方法强于线性规划方法和特征值分解方法.     

Boundary feedback stabilization of a Schr$\＂{o}$dinger equation interconnected with a heat equation

In this paper, we study stabilization for a Schoedinger equation, which is interconnected with a heat equation via boundary coupling. A direct boundary feedback control is adopted. By a detailed spectral analysis, it is found that there are two branches of eigenvalues： one is along the negative real axis, and the other is approaching to a vertical line, which is parallel to the imagine axis. Moreover, it is shown that there is a set of generalized eigenfunctions, which forms a Riesz basis for the energy state space. Finally, the spectrum-determined growth condition is held and the exponential stability of the system is then concluded.