一种自适应入位固持装置及试验研究

为解决飞机数字化装配中难以对机身大部件增加辅助固持并保持大部件位姿不变的技术难题,提出一种基于气浮和万向球座的大部件位姿跟随固持方法,并设计制造称之为随动定位器的专用柔性工装.结合某工程,进行定位器关键参数的分析计算和相关工艺试验研究,并对油压波动、相关零件磨损对锁紧力的影响以及芯轴自由端关键参数选择与入位可靠性问题进行了研究.结果表明,在芯轴角度偏差较小时,随动定位器可以在确保大部件位姿不被破坏的情况下,实现芯轴的小阻力自适应入位,并可以根据选定的工作油压和配合间隙可靠固持大部件,其性能可以满足工程要求.     

大港歧北斜坡三维地震深层目标精细处理及地质效果分析

歧北斜坡深层沙二、沙三段发育沿岸滩坝、辫状河水道及斜坡扇沉积体系。储层总体比较发育,但是横向变化大,单层厚度薄。现有地震资料横、纵向上地震分辨率低,无法满足砂体追踪和精细储层预测的要求。通过运用叠前反褶积、静校正、能量调整、叠后提高分辨率等技术,并实施处理解释一体化工作模式,处理质量过程控制等方法,使处理成果地震资料在保持地层波组特征不变的情况下,纵横向分辨率有了较大程度的提高,成像特征有了较大幅度的改善,基本上满足了地质需求。利用新处理的资料,通过井震结合,储层地球物理特征分析,在常规波阻抗反演的基础上,利用拟波阻抗反演的方法预测了沙二、三段各油组砂体的空间展布规律。取得了较好的地质效果。     

基于定向扩散的无线传感器网络拥塞控制方法

为了缓解无线传感器网络中多对一通信方式出现的拥塞问题,提出了一种基于定向扩散路由协议的拥塞控制方法.在该方法中,转发节点根据本地的拥塞信息调整速率;sink节点周期地检测网络中的拥塞状态并将拥塞信息通过逐跳的方式反馈到源节点,而源节点根据接收到的反馈信息调节速率.仿真实验表明,该算法能有效地缓解网络中出现的拥塞,保证数...     

水泥工业结构调整的特点及对人才的需求

我国是世界上最大的水泥生产国和消费国.目前水泥工业进入了结构调整阶段.随着我国经济和社会发展水平的提高,人们对资源和环境问题的重视,水泥工业的结构调整出现了新的特点,对人才的需求也出现了新的变化.     

显著性检测指导的高光区域修复

目的为解决传统的基于光照模型的高光修复算法无法很好地对高光区域存在饱和现象的单幅图像进行处理这一问题,提出一种显著性检测指导的高光区域修复算法。方法首先在亮度空间应用显著性模型,实现高光区域的自动检测和标记,之后运用改进的Exemplar-Based算法,综合利用图像的邻域和边缘信息,对标记的高光区域进行自适应修复,去除图像中的高光。结果分别对仿真及自然场景下的高光图像进行测试,实验结果表明,与原修复算法和传统高光去除算法相比,所提算法的修复效果更符合人眼视觉、修复后的图像质量更好。结论本文算法与Exemplar-Based算法及Tan方法相比,对高光区域存在饱和现象的单幅图像有较好的修复效果,并且有效地克服了传统高光去除算法受光照模型限制的缺点。     

Adaptive joint bandwidth and power allocation in heterogeneous wireless access environment

Joint bandwidth and power allocation for a multi-radio access(MRA)system in a heterogeneous wireless access environment is studied.Since both the number of users being served by the system and the wireless channel state are time-varying,the optimal resource allocation is no longer a static optimum and will change with the varying network state.Moreover,distributed resource allocation algorithms that require iterative updating and signaling interactions cannot converge in negligible time.Thus,it is unrealistic to assume that the active user number and the wireless channel state remain unchanged during the iterations.In this paper,we propose an adaptive joint bandwidth and power allocation algorithm based on a novel iteration stepsize selection method,which can adapt to the varying network state and accelerate the convergence rate.A distributed solution is also designed for the adaptive joint resource allocation implementation.Numerical results show that the proposed algorithm can not only track the varying optimal resource allocation result much more quickly than a traditional algorithm with fixed iteration stepsize,but can also reduce the data transmission time for users and increase the system throughput.     

基于高炉TRT系统控制技术的研究与改进

介绍高炉TRT控制系统的改进,以达到节能、降噪、环保的目的.     

基于改进AdaBoost算法的复杂网络链路预测

链路预测是复杂网络的重要研究方向,当前的链路预测算法因可利用的网络信息有限,导致预测算法的精确度受限。为了提高预测算法的性能,采用改进的AdaBoost算法进行链路预测。首先根据复杂网络样本建立邻接矩阵,完成样本的矩阵化处理;然后采用AdaBoost算法进行分类训练,通过权重投票获取预测结果;最后,考虑到复杂网络弱分类器预测正负误差分布的不均衡问题,设置权重调整因子η及其调整范围[η1,η2],并根据η值动态调整AdaBoost算法的多个弱分类器分类结果的权重,从而获得准确的链路预测结果。实验结果证明,相比其他常用网络链路预测算法及传统AdaBoost算法,改进的AdaBoost算法的预测准确率优势明显,且在节点数量较多时,其预测时间性能和其他算法的差距较小。     

基于侧重点聚类的数学表达式相似度计算方法

数学表达式相似度计算在信息检索中起着重要的作用,但现有的计算方法较少考虑数学表达式侧重点对相似度计算准确度的影响。为解决该问题,提出一种基于侧重点聚类的数学表达式相似度计算方法。针对侧重点主观性强的特点,定义表达式元素映射规则,使用[K]-means++算法对数学表达式聚类,从而归纳出数学表达式所属侧重点簇;以侧重点簇为依据,使用遗传算法对相似度计算方法中相关参数进行优化调节,以加强侧重点对相似度结果的影响。对比实验表明,该方法的相似度计算性能有所提高,得到的表达式结果列表更为理想。     

Consensus reaching for group decision making with multi-granular unbalanced linguistic information: A bounded confidence and minimum adjustment-based approach

In group decision making problems, there exist the situations that decision makers may use unbalanced linguistic term sets that are not uniformly and symmetrically distributed to provide their linguistic assessments over alternatives. Moreover, due to the difference in knowledge and culture backgrounds, it is also possible that multi-granular linguistic term sets may also be used by decision makers. How to manage multi-granular unbalanced linguistic information in consensus-based group decision making has becoming an important topic in linguistic decision making. In this paper, we first revise Herrera’s unbalanced linguistic term sets and propose a simplified linguistic computational model to fuse multi-granular unbalanced linguistic terms. Afterwards, for multi-criteria group decision making problems with multi-granular unbalanced linguistic information, we develop two optimization models to generate adjustment advice for decision makers who have to change his/her opinions in consensus reaching process, which consider both the bounded confidence levels and minimum adjustment of decision makers’ linguistic assessments. Moreover, an algorithm is further proposed to help decision makers reach consensus in group decision making. Eventually, an application example for ERP system supplier selection and some simulation results are presented to illustrate and justify the consensus reaching algorithm.