内隐学习的特征及对其本土教育的启示

内隐学习就是无意识获得刺激环境中复杂知识的过程。在无意识研究热潮中,内隐学习研究获得了很大的发展。内隐学习的研究对于理解人类认识过程的本质,特别是对于探明人们获得丰富复杂知识的心理机制提供了全新的视野。本文着重探讨内隐学习的特征以及对本土教育的启示。     

关于战时要人警卫的理性思考

随着国际政治、经济、军事的飞速发展,战时要人警卫安全已成为各国警卫部门研究和探讨的一个重要课题。根据战时要人警卫工作的特点和构成要素分析,战时要人警卫必须建立战时警卫联勤机制,强化战时警卫装备保障,锻造平战结合的警卫队伍,创新符合警卫实战要求的战法,以适应战时警卫工作需要。     

反潜编队应召搜索能力计算及效果评估

本文在分析反潜编队应召搜索特点的基础上,对应召搜索能力进行了必要的战术计算,对应召搜索的效果进行了评估,为实际反潜作战中提高对潜搜索的效果提供了可靠的依据。     

Detection of a Markovian target with optimization of the search efforts under generalized linear constraints

This paper deals with search for a target following a Markovian movement or a conditionally deterministic motion. The problem is to allocate the search efforts, when search resources renew with generalized linear constraints. The model obtained is extended to resource mixing management. New optimality equations of de Guenin's style are obtained. Practically, the problem is solved by using an algorithm derived from the FAB method. © 2002 Wiley Periodicals, Inc. Naval Research Logistics 49: 117–142, 2002; DOI 10.1002/nav.10009     

Algorithms for the multi‐item multi‐vehicles dynamic lot sizing problem

We consider a two‐stage supply chain, in which multi‐items are shipped from a manufacturing facility or a central warehouse to a downstream retailer that faces deterministic external demand for each of the items over a finite planning horizon. The items are shipped through identical capacitated vehicles, each incurring a fixed cost per trip. In addition, there exist item‐dependent variable shipping costs and inventory holding costs at the retailer for items stored at the end of the period; these costs are constant over time. The sum of all costs must be minimized while satisfying the external demand without backlogging. In this paper we develop a search algorithm to solve the problem optimally. Our search algorithm, although exponential in the worst case, is very efficient empirically due to new properties of the optimal solution that we found, which allow us to restrict the number of solutions examined. Second, we perform a computational study that compares the empirical running time of our search methods to other available exact solution methods to the problem. Finally, we characterize the conditions under which each of the solution methods is likely to be faster than the others and suggest efficient heuristic solutions that we recommend using when the problem is large in all dimensions. © 2005 Wiley Periodicals, Inc. Naval Research Logistics, 2006.     

文章编号：基于多目标进化搜索算法的AUV地磁仿生导航方法

针对水下自主航行器(AUV)地磁多参量多目标搜索的问题,提出了一种基于磁趋势敏感的多目标进化搜索算法。在进化算法的结构下,利用地磁场参量与导航路径的约束关系,以磁趋势敏感作为后验评估准则,建立导航模型,使得地磁多分量伴随航行器的运动同时同地收敛至各自目标值,实现导航目的。通过与六边形路径搜索算法的仿真对比,验证了多目标进化搜索算法的有效性和优越性。     

不确定条件下装备器材供应网规划模型

装备器材供应网是装备器材供应保障工作的重要基石,其规划问题是我军装备器材保障过程的重要战略决策之一。针对节点、边和需求的不确定性,对不确定条件下由多个区域供应子网构成的装备器材供应网的规划问题展开研究。针对问题的特点,用区间分析理论对供应网规划中的不确定性因素进行度量和运算,得到不确定性规划模型,通过区间运算转化,将不确定性模型转化为确定性混合整数规划模型,并设计采用基于禁忌搜索算法的两阶段算法进行求解,分别得到了不同参数设置下的模型求解结果,并将所用算法与模糊规划和随机规划算法的求解结果进行了比较分析。实例分析结果表明所建立的模型和算法具有较强的实用性。     

地磁仿生导航的多目标进化搜索算法

针对水下自主航行器地磁多参量多目标搜索的问题,提出一种基于磁趋势敏感的多目标进化搜索算法。在进化算法的结构下,利用地磁场参量与导航路径的约束关系,以磁趋势敏感作为后验评估准则,建立导航模型,使得地磁多分量伴随航行器的运动同时同地收敛至各自目标值,实现导航目的。通过与六边形路径搜索算法的仿真对比,验证了多目标进化搜索算法的有效性和优越性。     

结合像素局部对比度的直线特征检测算法

鲁棒高效的直线提取算法在空间目标位姿估计、跟踪、骨架重建等领域有广泛的应用。提出基于像素局部对比度和全局虚警抑制的直线段检测算法。算法分为四步:第一步,计算像素点的梯度以及局部对比度;第二步,将方向大致相同的像素点分成直线支撑区域(像素方向为像素梯度方向的顺时针垂直方向),并对支撑区域进行矩形近似;第三步,在直线支撑区域内拟合直线段,计算直线参数;第四步,根据直线支撑区域信息验证直线段,抑制虚警。实验测试结果表明:该算法在复杂条件下,特别是光照影响条件下,具有更好的鲁棒性和效率。     

Continuous accumulation games on discrete locations

In an accumulation game, a HIDER attempts to accumulate a certain number of objects or a certain quantity of material before a certain time, and a SEEKER attempts to prevent this. In a continuous accumulation game the HIDER can pile material either at locations $1, 2, …, n, or over a region in space. The HIDER will win (payoff 1) it if accumulates N units of material before a given time, and the goal of the SEEKER will win (payoff 0) otherwise. We assume the HIDER can place continuous material such as fuel at discrete locations i = 1, 2, …, n, and the game is played in discrete time. At each time k > 0 the HIDER acquires h units of material and can distribute it among all of the locations. At the same time, k, the SEEKER can search a certain number s < n of the locations, and will confiscate (or destroy) all material found. After explicitly describing what we mean by a continuous accumulation game on discrete locations, we prove a theorem that gives a condition under which the HIDER can always win by using a uniform distribution at each stage of the game. When this condition does not hold, special cases and examples show that the resulting game becomes complicated even when played only for a single stage. We reduce the single stage game to an optimization problem, and also obtain some partial results on its solution. We also consider accumulation games where the locations are arranged in either a circle or in a line segment and the SEEKER must search a series of adjacent locations. © 2002 John Wiley & Sons, Inc. Naval Research Logistics, 49: 60–77, 2002; DOI 10.1002/nav.1048