飞行器与机器人的区域目标搜索最优控制

描述了飞行器导航或移动机器人的区域搜索控制问题.为了使该问题得到优化解决,首先建立了基于区域搜索控制问题的模型,将最优控制原理运用于此模型上,得到其伴随方程和控制方程,后基于此分析了该问题,且讨论了此方法的可行性.然后,通过解出问题的规范方程,使飞行器导航或移动机器人的区域搜索控制问题最终得以解决,进而推导得到了飞行器导航或移动机器人的区域目标搜索最优控制以及最优轨线.最后,通过计算仿真结果表明,该方法是有效的,故为飞行器导航与移动机器人的区域目标搜索最优控制提供了依据.     

Bad-scenario-set robust scheduling for a job shop to hedge against processing time uncertainty

This paper proposed two robust scheduling formulations in real manufacturing systems based on the concept of bad scenario set to hedge against processing time uncertainty, which is described by discrete scenarios. Two proposed robust scheduling formulations are applied to an uncertain job-shop scheduling problem with the makespan as the performance criterion. The united-scenario neighbourhood (UN) structure is constructed based on bad scenario set for the scenario job-shop scheduling problem. A tabu search (TS) algorithm with the UN structure is developed to solve the proposed robust scheduling problem. An extensive experiment was conducted. The computational results show that the first robust scheduling formulation could be preferred to the second one for the discussed problem. It is also verified that the obtained robust solutions could hedge against the processing time uncertainty through decreasing the number of bad scenarios and the degree of performance degradation on bad scenarios. Moreover, the computational results demonstrate that the developed TS algorithm is competitive for the proposed robust scheduling formulations.     

基于蒙特卡洛树搜索的数值目标子群发现算法

MonteCloPi算法是一种基于蒙特卡洛树搜索(Monte Carlo tree search, MCTS)的任意时间子群发现算法,旨在使用MCTS策略构建非对称的最佳优先搜索树来发现高质量的多样性模式集,但是限制了目标为二值变量.为此,本文结合了数值目标的特点,通过为置信度上界(upper confidence bound, UCB)公式选取合适的C值、动态调整各个样本的拓展权重并对搜索树进行剪枝、使用自适应top-k均值更新策略,将MonteCloPi算法拓展到了数值目标.最后,在UCI数据集、全国健康与营养调查(national health and nutrition examination survey, NHANES)听力测试数据集上的实验结果表明本文的算法相比其他算法可以发现更高质量的多样性模式集,并且最优子群的可解释性也更好.     

一种基于语义网的相似度计算模型

在检索信息时我们经常简单的依靠关键词匹配,往往导致检索结果不全或者不准。随着语义网概念的提出,为我们提供了新的研究方向。本文在传统的计算句子相似度的基础上,提出了把语义网和改进的相似度计算方法相结合,并把该计算模型应用在依靠论文摘要来检索相关论文上。由于语义网的引入,使得搜索变得智能化,从简单的依靠关键词匹配提高到语义层面,从而提高了查全率和查准率。     

Fixed-time sliding mode control based plant/controller co-design of dual-motor driving system

A fixed-time sliding mode controller based plant/controller co-design scheme is developed for dual-motor driving systems. The proposed controller is fixed-time stable subject to unknown disturbances which guarantees the robustness of the proposed control scheme and a less conservative solution can be ensured by comparing with the conventional fixed-time convergence technique. Due to the existence of couplings between the plant and the controller, traditional design procedures in which the plant and the controller are designed sequentially and separately cannot guarantee the overall optimum of control systems. A co-design scheme based on the nested optimisation strategy is developed in this paper. With the nested optimisation strategy, the co-design solution can be achieved efficiently and reliably. A combined cost function considering both the plant and the controller is developed so that the largest load can be achieved without degrading the control performance. The fixed-time convergent controller is employed and considered into the co-design scheme. The gravitational search algorithm is adopted to optimise controller parameters in the co-design scheme. With the presented co-design method, the largest load of the studied system can be achieved with the satisfactory control performance. Contrastive Simulation and experimental results demonstrate the efficacy of the proposed controller and co-design scheme.     

基于随机森林回归的清防垢加药量预测方法

复合驱由于强碱化学剂的注入易造成严重的结垢现象,而预测清防垢加药量是制定科学的清防垢方案的关键.为了获得一种具有较强实用价值和较高预测精度的复合驱清防垢加药量的预测方法,该文将随机森林回归算法应用到复合驱清防垢加药量预测.首先,分析并处理影响清防垢加药量的20维特征,利用随机森林回归的特征重要性评估功能对影响加药量的众...     

一种改进的折半查找算法

针对查找范围变化很大而又相对稳定的查找对象,给出了一种改进的基于区间控制的折半查找算法,当后一个查找对象在前一个查找对象附近时,在最坏状态和平均状态下,该算法与传统的标准折半查找算法相比,其查找长度显著减少,查找速度快,当父表很大而子表相对很小时,存储上仅需增加一个额外的存储单元,实现代价很小。此算法适用于过程控制中的实时查找处理,有一定的实用价值。     

对ORL人脸数据库识别过程中的参数选择策略

对ORL人脸数据库的识别大致分为两步骤:使用PCA对训练集降维提取特征向量和使用KNN对样本集进行分类。在该过程中,有两个参数直接影响着人脸识别的准确率:PCA选取的特征向量数目n和KNN中的k值。如果对它们的选取没有一个良好的策略,就会出现正确率太低、时间复杂度太高、过拟合等问题。文章采用状态空间搜索找到准确率与时间复杂度中的平衡点,得到了有效的搜索结果。     

线搜索(LS)共轭梯度法非单调算法的全局收敛性

非单调线搜索技巧在非线性优化中得到成功的应用与扩展,非单调线搜索下的共轭梯度法则可以提高大规模非线性优化问题的收敛速度。对LS共轭梯度法做了某些变型,在非单调线搜索下,该方法保证每次迭带都会产生下降的方向,在较弱的条件下得到算法全局收敛性。     

The Full Cost of Cryptanalytic Attacks

An open question about the asymptotic cost of connecting many processors to a large memory using three dimensions for wiring is answered, and this result is used to find the full cost of several cryptanalytic attacks. In many cases this full cost is higher than the accepted complexity of a given algorithm based on the number of processor steps. The full costs of several cryptanalytic attacks are determined, including Shanks method for computing discrete logarithms in cyclic groups of prime order n, which requires n^1/2+o(1) processor steps, but, when all factors are taken into account, has full cost n^2/3+o(1). Other attacks analyzed are factoring with the number field sieve, generic attacks on block ciphers, attacks on double and triple encryption, and finding hash collisions. In many cases parallel collision search gives a significant asymptotic advantage over well-known generic attacks.