控制系统模型简化及参数寻优的仿真

本文应用随机数直接搜索的单纯形最优化方法将系统高阶模型简化为低阶等效模型，并对控制系统调节器参数进行在线寻优，该方法的主要特点是：编程简单，有较宽的初值选择范围，搜索的结果可靠。     

Reactive Search strategies using Reinforcement Learning,local search algorithms and Variable Neighborhood Search

Optimization techniques known as metaheuristics have been applied successfully to solve different problems, in which their development is characterized by the appropriate selection of parameters (values) for its execution. Where the adjustment of a parameter is required, this parameter will be tested until viable results are obtained. Normally, such adjustments are made by the developer deploying the metaheuristic. The quality of the results of a test instance [The term instance is used to refer to the assignment of values to the input variables of a problem.] will not be transferred to the instances that were not tested yet and its feedback may require a slow process of “trial and error” where the algorithm has to be adjusted for a specific application. Within this context of metaheuristics the Reactive Search emerged defending the integration of machine learning within heuristic searches for solving complex optimization problems. Based in the integration that the Reactive Search proposes between machine learning and metaheuristics, emerged the idea of putting Reinforcement Learning, more specifically the Q-learning algorithm with a reactive behavior, to select which local search is the most appropriate in a given time of a search, to succeed another local search that can not improve the current solution in the VNS metaheuristic. In this work we propose a reactive implementation using Reinforcement Learning for the self-tuning of the implemented algorithm, applied to the Symmetric Travelling Salesman Problem.     

一种基于改进Hash函数的LTE ePDCCH搜索空间的设计

对于LTE的ePDCCH来说,从eCCE到PRB的映射没有交织器,如果沿用PDCCH的Hash函数进行搜索空间的随机化处理,会造成搜索空间在频域资源上过分集中,对集中式ePDCCH的性能产生负面影响.为使ePDCCH的搜索空间尽量遍布在所有可能的ePDCCH资源上,对PDCCH的Hash函数进行改进,以对集中式ePDCCH的搜索空间进行随机化处理.仿真结果表明,该方法可有效提高ePDCCH频选调度的效率,降低ePDCCH连续调度阻塞的概率.     

一种基于区间约束的折半查找算法

针对变化范围很大而又相对稳定的查找对象,给出一种基于区间约束的折半查找算法。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,该算法与标准的折半查找算法比较,其查找长度元旦显著减少,而且代价很小。此算法适合用于类似过程控制中的对低频信号的实时查有处理,并在国家级新产品WPJ－3微机频率事故记录装置和WQP－4微机频率继电器中得到了成功的应用。     

Design of an Intelligent Meta Search Engine

The rapid development of the WWW has made the exploration of new types of Search Engine become the urgent problem in the process of the Web development. Combining the latest development of information search and AI, the author in this paper puts forward a new solution： Web Intelligence Meta Search. Based on the review of the current technology of search engine, the author firstly brings forward the basic framework of the Intelligence Meta Search, and introduces the key technologies to realize it in detail, including Textual Study, Indicative Technology of Chinese Words, Information Filtration, Individual User Modeling, etc. in the machine learning.     

Relaxed multi-way trees with group updates

Data structures with relaxed balance differ from standard structures in that rebalancing can be delayed and interspersed with updates. This gives extra flexibility in both sequential and parallel applications. We study the version of multi-way trees called (a,b)-trees (which includes B-trees) with the operations insertion, deletion, and group insertion. The latter has applications in for instance document databases, WWW search engines, and differential indexing. We prove that we obtain the optimal asymptotic rebalancing complexities of amortized constant time for insertion and deletion and amortized logarithmic time in the size of the group for group insertion. These results hold even for the relaxed version. This is an improvement over the existing results in the most interesting cases.     

DRSP--一种高效可靠的MA定位协议

在MA系统中,为了使参与的MA更好地进行协作,以及使移动的MA可以准确快速地被找到,一个动态MA定位协议是必不可少的。它不仅要满足传统分布式系统的透明、可规划和有效等特性,还要满足MA系统中保持MA环境的连续一致要求。本文提出的DRSP是一个具有以上特征的MA定位协议,不仅给出了具体的协议内容,而且通过一个具体的搜索程序证明了DRSP的连续性和一致性。 更多还原     

基于GATS贝叶斯网络结构学习的航班延误模型

对遗传算法（GA）贝叶斯网络（BN）结构学习和禁忌搜索算法（TS）进行分析,提出遗传禁忌搜索贝叶斯网络结构学习算法GATS_BNSL。把禁忌搜索思想引入到遗传算法BN结构学习由父代种群产生后代种群的演化过程中,以禁忌搜索交叉和禁忌搜索变异改进传统的遗传算子,对比实验分析表明了GATS_BNSL的学习优势。应用此方法,基于真实数据,建立了大型枢纽机场航班离港延误模型。该模型切实反映了导致航班延误的多因素之间的因果关系,而且建模时间少,学习正确率高。     

Semplore: A scalable IR approach to search the Web of Data

The Web of Data keeps growing rapidly. However, the full exploitation of this large amount of structured data faces numerous challenges like usability, scalability, imprecise information needs and data change. We present Semplore, an IR-based system that aims at addressing these issues. Semplore supports intuitive faceted search and complex queries both on text and structured data. It combines imprecise keyword search and precise structured query in a unified ranking scheme. Scalable query processing is supported by leveraging inverted indexes traditionally used in IR systems. This is combined with a novel block-based index structure to support efficient index update when data changes. The experimental results show that Semplore is an efficient and effective system for searching the Web of Data and can be used as a basic infrastructure for Web-scale Semantic Web search engines.     

On the structure of systematic prefix codes

Systematic prefix codes play an important role in coding theory, we relate them with the problem of the partition of a free (sub-) monoid into two free sub-monoids. We show too that among the dual codes of a systematic prefix code A there exists one and only one which appears in the automaton recognizing A ^*. The characterization of this automaton and some corollaries stated here will allow us to show in further note that systematic prefix codes are involved in the structure of any regular prefix code. Work done under CNR contract No. R-l7-02-417-0-A.