基于遗传算法的落差指数法参数优选

利用遗传算法的全局寻优能力，对落差指数法中的参数进行优化，通过实例分析表明，这种方法是可行的，且能弥补传统作法中的不足，值得推广。     

N皇后问题的启发式算法探讨

搜索策略的选择与设计是人工智能领域问题求解的核心问题之一,直接影响到问题求解过程中存储空间的占用和计算的复杂性,影响到问题求解的效率。在给出N皇后问题形式化描述和现有搜索算法的基础上,设计了3种解决N皇后问题的启发式算法,并将其与深度优先和宽度优先等搜索策略进行了分析和比较,得出了几点关于设计启发式算法的启示。     

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.     

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。     

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.     

Composing fifth species counterpoint music with a variable neighborhood search algorithm

In this paper, a variable neighborhood search (VNS) algorithm is developed and analyzed that can generate fifth species counterpoint fragments. The existing species counterpoint rules are quantified and form the basis of the objective function used by the algorithm. The VNS developed in this research is a local search metaheuristic that starts from a randomly generated fragment and gradually improves this solution by changing one or two notes at a time. An in-depth statistical analysis reveals the significance as well as the optimal settings of the parameters of the VNS. The algorithm has been implemented in a user-friendly software environment called Optimuse. Optimuse allows a user to input basic characteristics such as length, key and mode. Based on this input, a fifth species counterpoint fragment is generated by the system that can be edited and played back immediately.     

Efficient Evaluation of Monitoring Top-t Most Influential Places

The continuous top-t most influential place (CTtMIP)query is defined formally and solved efficiently in this paper.A CTtMIP query continuously monitors the t places with the maximum influence from the ...     

Inter-antenna and subblock shifting and inversion for peak-to-average power ratio reduction in MIMO-OFDM systems

In this article, an inter-antenna inter-subblock shifting and inversion (IASSI) scheme is proposed to reduce the peak-to-average power ratio (PAPR) in multi-input multi- output orthogonal frequency division multiplexing (MIMO- OFDM) systems. It exploits multiple antennas and subblocks to provide additional degrees of freedom to benefit the system. To reduce the implementation complexity of the proposed scheme, two simple suboptimal schemes are further presented based on the minimum current maximum criterion; one adopts sequential search and the other employs random binary grouping. The simulation results exhibit the effectiveness of these proposed schemes.     

基于禁忌搜索算法的系统辨识

本文研究了禁忌搜索算法解决系统辨识问题的可行性。首先将系统辨识问题转化为参数空间上的优化问题,然后利用禁忌搜索算法求取优化问题的最优解以获得系统参数的最优估计。分别通过对离散和连续系统的仿真研究,表明了本方法的可行性。并与其它方法进行了比较,结果表明本方法在搜索全局最优和克服噪音上都具有很好的效果。