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11.
Making optimal use of available resources has always been of interest to humankind, and different approaches have been used in an attempt to make maximum use of existing resources. Limitations of capital, manpower, energy, etc., have led managers to seek ways for optimally using such resources. In fact, being informed of the performance of the units under the supervision of a manager is the most important task with regard to making sensible decisions for managing them. Data envelopment analysis (DEA) suggests an appropriate method for evaluating the efficiency of homogeneous units with multiple inputs and multiple outputs. DEA models classify decision making units (DMUs) into efficient and inefficient ones. However, in most cases, managers and researchers are interested in ranking the units and selecting the best DMU. Various scientific models have been proposed by researchers for ranking DMUs. Each of these models has some weakness(es), which makes it difficult to select the appropriate ranking model. This paper presents a method for ranking efficient DMUs by the voting analytic hierarchy process (VAHP). The paper reviews some ranking models in DEA and discusses their strengths and weaknesses. Then, we provide the method for ranking efficient DMUs by VAHP. Finally we give an example to illustrate our approach and then the new method is employed to rank efficient units in a real world problem. 相似文献
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社会选择理论是研究如何表达和聚合个体选择的一门学问.而社会选择理论与计算机科学的融合产生了称为计算社会选择的交叉学科,该学科成为社会计算的重要研究内容之一,在人工智能、经济和计算性理论领域引起了轰动.其一方面引入了复杂性分析和算法设计等计算机学科中常用的技术来对社会选择机制进行研究;另一方面也通过引入社会选择理论中的概念来推动计算机技术的发展,特别是在多智能体系统研究中有着成功的应用.投票理论是计算社会选择中最重要的研究主题之一.首先介绍常见的投票方法以及投票理论的形式化框架;再对投票理论中所关心的操纵问题做分析;然后介绍在组合域上的投票;最后对其他相关问题作简要介绍,并对该领域未来的发展与应用做出展望. 相似文献
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以EM算法为基础,在给定贝叶斯网络结构情况下。研究分析了Voting EM算法并利用该算法对防洪决策贝叶斯网络进行在线参数学习,将该算法与EM算法的学习结果进行了比较分析,结果表明Voting EM算法不但能够进行在线参数学习,而且也具有较高的学习精度. 相似文献
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矿井视频监控由于受到井下光照不均匀、高浓度粉尘、成像器件电压不稳定等因素的影响,导致实时获取的图像对比度不高且含有大量的颗粒状噪声,严重影响对图像的准确判读与分析。为此,对经典中值滤波算法进行了改进,提出了一种融合噪声检测策略与投票统计学原理的改进型中值滤波算法。首先对获取的原始矿井视频监控图像采用双平台直方图均衡化算法(Double platform histogram equalization,DPHE)进行处理,该算法通过对图像各灰度级对应的像素点数目设定2个阈值(平台值)对图像背景信息进行抑制,对图像细节信息进行增强;然后将增强后的图像划分为多个规则图像块,根据各图像块内像素点灰度值的分布特征设计了一种噪声图像块自适应检测方法,若某图像块内的灰度值异常点数目超过一定限值,则该图像块被标记为噪声图像块;最后,对噪声图像块进行投票中值滤波。采用C++语言对所提算法进行了编程,并采用2幅采集于某煤矿井下综采工作面的视频监控图像进行试验,结果表明:所提算法对于不同失真程度的矿井视频监控图像的处理效果优于中值滤波、直方图均衡化等算法,对于最大限度地发挥矿井视频监控系统的作用有一定的参考价值。 相似文献
15.
The voting system studied consists of n voting units each either providing a binary decision (0 or 1) or abstaining from voting. The system output is 1 if the cumulative weight of all 1-opting units is at least a pre-specified fraction τ of the cumulative weight of all non-abstaining units. Otherwise, the system output is 0.In this paper, we study the effect of limited availability of the voting units on the entire voting system reliability. Two different types of systems are considered. In the system of type 1, the absence of unit output (unit unavailability) is interpreted by the system as abstention from voting. In the system of type 2, the unavailable state of the voting unit and its abstention from voting can be distinguished and the system parameters can be adjusted to optimize its performance for each combination of available units.There are two ways to improve reliability of weighted voting system consisting of units with the given output probability distribution: optimization of system parameters (weights of units and threshold factor value) and units availability enhancement (for example, by choosing proper maintenance policy). This paper shows a method of incorporating information about units' availability into a procedure for determining the optimal system parameters. It also presents a method for determining indices that measure importance of voting units availability for both types of systems. These indices indicate voting units for which efforts of availability enhancement are the most beneficial from the entire system reliability improvement point of view.The approach is based on using a universal generating function technique and optimization procedure presented in [5]. Examples are presented. 相似文献
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互联网应用已经渗透到人们日常生活的方方面面,恶意URL防不胜防,给人们的财产和隐私带来了严重威胁。当前主流的防御方法主要依靠黑名单机制, 难以检测 黑名单以外的URL。因此,引入机器学习来优化恶意URL检测是一个主要的研究方向,但其主要受限于URL的短文本特性,导致提取的特征单一,从而使得检测效果较差。针对上述挑战,设计了一个基于威胁情报平台的恶意URL检测系统。该系统针对URL字符串提取了结构特征、情报特征和敏感词特征3类特征来训练分类器,然后采用多分类器投票机制来判断类别,并实现威胁情报的自动更新。实验结果表明,该方法对恶意URL进行检测 的准确率 达到了96%以上。 相似文献
20.
In this paper, we propose a new mechanism for counteracting ARP (Address Resolution Protocol) poisoning-based Man-in-the-Middle (MITM) attacks in a subnet, where wired and wireless nodes can coexist. The key idea is that even a new node can be protected from an ARP cache poisoning attack if the mapping between an IP and the corresponding MAC addresses is resolved through fair voting among neighbor nodes under the condition that the number of good nodes is larger than that of malicious nodes. Providing fairness in voting among the nodes that are heterogeneous in terms of the processing capability and access medium is quite a challenge. We attempt to achieve fairness in voting using the uniform transmission capability of Ethernet LAN cards and smaller medium access delays of Ethernet than for wireless LAN. Although there is another scheme that resolves the same issue based on voting, i.e. MR-ARP, the voting fairness is improved further by filtering the voting reply messages from the too-early responding nodes, and the voting-related key parameters are determined analytically considering the fairness in voting. This paper shows that fairness in voting can be achieved using the proposed approach, overcoming the limitations of other voting-based schemes, and ARP poisoning-based MITM attacks can be mitigated in a more generalized environment through experiments. 相似文献