A hybrid formulation for treatment of point-wise state variable constraints in dynamic response optimization

This paper presents methods of design sensitivity analysis and optimization of dynamic response of mechanical and structural systems. The point-wise state variable constraint function is divided into time sub-domains such that each sub-domain contains only one local maximum point. Then, the original constraint is replaced by a number of equivalent functional constraints. Each functional constraint is the integration of the positive value of the original constraint over its own time sub-domain. A direct differentiation method and three adjoint variable methods of design sensitivity analysis are presented. All of these methods are discussed and compared. It turns out that two of the adjoint variable methods are more efficient than others. A hybrid optimization algorithm based on these methods is proposed in detail. Two problems are solved for optimal design. Comparisons of results with those available in the literature are made. Numerical experience with the proposed method is discussed in detail. It is concluded that the new formulation is extremely efficient and converges to either optimal or near optimal solutions without any difficulty.     

Mining minimal distinguishing subsequence patterns with gap constraints

Discovering contrasts between collections of data is an important task in data mining. In this paper, we introduce a new type of contrast pattern, called a Minimal Distinguishing Subsequence (MDS). An MDS is a minimal subsequence that occurs frequently in one class of sequences and infrequently in sequences of another class. It is a natural way of representing strong and succinct contrast information between two sequential datasets and can be useful in applications such as protein comparison, document comparison and building sequential classification models. Mining MDS patterns is a challenging task and is significantly different from mining contrasts between relational/transactional data. One particularly important type of constraint that can be integrated into the mining process is the gap constraint. We present an efficient algorithm called ConSGapMiner (Contrast Sequences with Gap Miner), to mine all MDSs satisfying a minimum and maximum gap constraint, plus a maximum length constraint. It employs highly efficient bitset and boolean operations, for powerful gap-based pruning within a prefix growth framework. A performance evaluation with both sparse and dense datasets, demonstrates the scalability of ConSGapMiner and shows its ability to mine patterns from high dimensional datasets at low supports.     

Loop‐Shaping Design Of Pid Controllers With Constant Ti/Td RATIO

This paper presents new tuning rules for PID controllers based on loop shaping. Previous research has shown that maximization of the integral gain subject to constraints on the maximum sensitivity is an efficient design method for PI controllers, but that additional constraints are needed for design of PID controllers. In this paper, an additional constraint is obtained by restricting the ratio between integral time and derivative time. It is shown that this gives a numerically efficient method that gives good results for a large class of processes.     

信息安全管理系统的组卷算法研究

针对信息安全系统对问卷的要求,分析了组卷的约束条件,建立了组卷的数学模型,并提出了改进的遗传算法求解纽卷问题的新方法。实验结果表明,所提出的新算法相对于传统算法更加有效,组卷成功率高,具有较好的性能和实用性。     

几何约束有向图的规划分解研究

在基于有向图表达的几何约束系统中,几何约束的匹配方向、分布状态以及有向图中强连通分量的规模直接影响到整个约束系统的求解;如何对几何约束系统进行合理规划,得到正确有效的求解序列,是目前约束分解研究的重要内容。该文提出了一个规划分解算法,它针对欠约束几何系统的特点,能够优化约束的初始匹配方向,对于约束匹配过程中生成的强连通子图,通过调整约束匹配方向,自适应地改善约束分布,从而减小强连通子图的规模,以求得到几何约束系统正确而高效的求解序列。同时,基于规划分解算法,完成了约束的奇异性分析,提供了面向分解的奇异性分析算法。     

一种非参数惩罚函数的优化演化算法

对约束优化问题的处理通常使用惩罚函数法，使用普通惩罚函数法的困难存在于参数的选取。该文提出一种基于演化算法的非参数罚函数算法，对违反约束条件动态地进行惩罚，由适应值的设定来平衡群体中可行解和不可行解的比例，使群体较好地向最优解逼近，使用实数编码的多父体单形杂交演化策略来实现新算法，通过对测试函数的检验，该算法具有稳健、高效、简洁易于实现等特点。     

分布式复式数据流的处理

在分布式数据流环境中，系统的通信带宽是一种瓶颈资源．在保证查询精度的前提下，为了有效地减少网络中数据流的传输量，提出了一种新的数据流传输方式，称为复式数据流．复式数据流方法是将分布式数据流系统中的原始数据流分组合并成复式数据流之后再进行传输．在定义了复式数据流的基础上，给出了复式数据流的生成算法，并且分析了基于复式数据流的查询操作的误差度，讨论了构造复式数据流的相关问题，最后通过实验验证了这种方法的有效性．     

二维全约束优化算法的研究

从工程实际出发，分析了现有的几何约束求解方法中存在的问题，提出了一种新的二维全约束优化算法。该方法采用自由度优先搜索策略生成有向图，用简单推理和代数方程组综合方法求解，较好地解决了满约束求解和过约束判断问题，大大减少了非线性方程组的规模，使得约束问题的求解得到简化，提高了求解效率。     

Vague熵的约束条件和新模糊熵的构造

Vague集合的模糊熵既应包含Vague集的未知性又含有本身的不确定性。分析了现有Vague熵约束条件和构造方法上存在的缺陷,提出改进的Vague熵约束条件和Vague熵的公理化定义,给出一种新的Vague熵的构造方法,通过算例比较,指出这种新的模糊熵更加合理,更符合人们的直觉。     

Design of sampled-data critical control systems based on the fast-discretization technique

The fast-discretization is known as an approximate but efficient technique for design and analysis of sampled-data systems. In this paper, we propose a fast-discretization-based design for sampled-data critical control systems. Supposing a tracking problem or a slow-changing disturbance rejection problem, we assume that an exogenous input is a persistent and/or transient input with bound on the rate of change. It is shown that the critical constraint for such exogenous inputs can be given in the form of the inequality constraint on the unit step response. The design parameters are determined by a numerical search method subject to this constraint. However, instead of evaluating it strictly, we check the corresponding constraint which is obtained from the fast-discretized system. Although this approach is approximate, it provides an efficient numerical procedure for a computer-aided design. To show the validity of the proposed method, an example of a multi-objective critical control system design is presented.