基于LDA的互联网广告点击率预测研究

广告点击率是互联网广告投放的重要依据,有效地预测广告的点击率,对于提高广告投放的效率有着至关重要的作用。在训练点击率预测模型的过程中,往往面临着广告及用户的数量巨大以及训练数据集稀疏的问题,从而导致点击率预测的准确度下降。针对这些问题提出了一种基于LDA (Latent Dirichlet Allocation)的点击率预测算法,即LDA-FMs,该算法对原有训练集进行基于主题的分割,利用分割后的子训练集分别建立不同主题下的点击率预测模型,在此基础上,利用广告属于不同主题的概率,有权重的结合每个预测模型的预测结果,进而计算广告的点击率。实验基于KDD Cup 2012-Track2的真实数据集,证明了算法的可行性与有效性。     

基于阈值滑动窗口机制的虚拟机迁移判决算法

数据中心是云计算中数据运算、交换、存储的中心。近年来以虚拟机为粒度的虚拟机放置管理成为云数据中心能耗管理、实现动态可伸缩资源提供的重要支撑技术。在虚拟机放置的动态管理阶段,虚拟机迁移触发机制主要是根据物理主机中资源利用率的变化情况,决定是否需要将虚拟机迁移到其它主机。迁移时机判决准确能够有效地平衡过热点并关掉过冷点。当前的迁移时机缺乏对整个数据中心负载变化行为趋势的反映,也因为静态的阈值设定容易发生频繁的迁移,造成不必要的迁移代价和传输开销。提出了基于阈值滑动窗口机制的虚拟机迁移判决算法(iWnd),其能够根据整个数据中心任务量的多少动态调整高低阈值间窗口的大小,减少了任务量满负荷时期需要迁移虚拟机的数量,从而避免不必要的迁移开销和传输代价,有效地实现节能。在云计算平台Cloudsim上进行了仿真实验。结果表明,提出的iWnd算法在减少虚拟机迁移数量、降低迁移失败率上有良好的效果,同时并未产生过多额外的功耗。     

一种基于虚拟力的分布式Voronoi控制策略

针对无线移动传感器网络在目标区域的覆盖问题,提出了一种基于移动距离的局部分布式算法,利用Voronoi多边形的特征对目标区域进行有效的分割,运用力学的矢量概念,根据Voronoi图的边和顶点确定虚拟力的方向和大小即节点的移动方向和距离,提出了基于移动距离的分布式Voronoi控制算法,以确定节点移动状态。仿真实验表明,所提算法不仅使得节点在目标区域实现了高覆盖率,同时在时间上也较早地达到了收敛,优化了网络的覆盖控制。     

Optimal replacement policy for a two-dissimilar-component cold standby system with different repair actions

In this paper, a cold standby repairable system consisting of two dissimilar components and one repairman is studied. When failures occur, the repair of both component 1 and component 2 are not ‘as good as new’. The consecutive operating times of component 1 after repair constitute a decreasing geometric process, while the repair times of component 1 are independent and identically distributed. For component 2, its failure is rectified by minimal repair, and the repair time is negligible. Component 1 has priority in use when both components are good. The replacement policy N is based on the failure number of component 1. Under policy N, we derive the explicit expression of the long-run average cost rate C(N) as well as the average number of repairs of component 2 before the system replaced. The optimal replacement policy N*, which minimises the long-run average cost rate C(N), is obtained theoretically. If the failure rate r(t) of component 2 is increasing, the existence and uniqueness of the optimal policy N* is also proved. Finally, a numerical example is given to validate the developed theoretical model. Some sensitivity analyses are provided to show the influence of some parameters, such as the costs for replacement and repair, and the parameters of the lifetime and repair time distributions of both components, to the optimal replacement policy N* and corresponding average cost rate C(N*).     

Containment control of multi-agent systems with unbounded communication delays

In this paper, we address the containment control problem for multi-agent systems under heterogeneous unbounded communication delays with emphasis on the convergence rate analysis. Different from most works on multi-agent systems, we resort to a viewpoint from the area of positive delay systems. We first cast the containment control problem into the stability analysis of an associated error system. In order to capture the convergence rate, we introduce a nondecreasing positive function whose reciprocal represents the decay rate of the associated error system. Under the assumption that each follower has access to at least one leader and some mild hypotheses on the communication delays, an explicit condition is given to characterise the decay rate of the associated error system in terms of linear programming. In addition, we provide several special cases when the communication delays are restricted by linear, sublinear and logarithmic growth rates, respectively. Finally, through numerical examples, it is shown that the convergence rate is dominated by the delays being the highest order infinitely large quantity.     

Optimal number of minimal repairs with cumulative repair cost limit for a two-unit system with failure rate interactions

A discrete replacement model is presented that includes a cumulative repair cost limit for a two-unit system with failure rate interactions between the units. We assume a failure in unit 1 causes the failure rate in unit 2 to increase, whereas a failure in unit 2 causes a failure in unit 1, resulting in a total system failure. If unit 1 fails and the cumulative repair cost till to this failure is less than a limit L, then unit 1 is repaired. If there is a failure in unit 1 and the cumulative repair cost exceeds L or the number of failures equals n, the entire system is preventively replaced. The system is also replaced at a total failure, and such replacement cost is higher than the preventive replacement cost. The long-term expected cost per unit time is derived using the expected costs as the optimality criterion. The minimum-cost policy is derived, and existence and uniqueness are proved.     

基于Seam Carving的图像放大算法研究与改进

针对Seam Carving图像放大算法中,能量值前k小的像素带可能出现共用点的情况,提出了一种改进的图像放大自适应算法,通过判断图像中出现共用点的像素带的情况及计算其共用率的值,经过一定的策略确定待新增的像素带位置,该算法使得图像中视觉关注非重要信息区域像素带的增加能得到较均匀的分布;实现了人工干预选择视觉关注重要区域的方法,避免了自适应算法本身因误判视觉关注重要区域而带来关注对象发生变形扭曲的情况.实验证明,改进的算法能得到更好的放大效果.     

Performance Analysis of The Auxiliary‐Model‐Based Multi‐Innovation Stochastic Newton Recursive Algorithm for Dual‐Rate Systems

The stochastic Newton recursive algorithm is studied for dual‐rate system identification. Owing to a lack of intersample measurements, the single‐rate model cannot be identified directly. The auxiliary model technique is adopted to provide the intersample estimations to guarantee the recursion process continues. Intersample estimations have a great influence on the convergence of parameter estimations, and one‐step innovation may lead to a large fluctuation or even divergence during the recursion. In the meantime, the sample covariance matrix may appear singular. The recursive process would cease for these reasons. In order to guarantee the recursion process and to also improve estimation accuracy, multi‐innovation is utilized for correcting the parameter estimations. Combining the auxiliary model and multi‐innovation theory, the auxiliary‐model‐based multi‐innovation stochastic Newton recursive algorithm is proposed for time‐invariant dual‐rate systems. The consistency of this algorithm is analyzed in detail. The final simulations confirm the effectiveness of the proposed algorithm.     

基于LASSO回归模型的网贷借款成功影响因素挖掘

随着P2P网络借贷交易量的增大,对P2P交易数据的挖掘和分析备受关注,其中一项重要的研究课题是网络借款成功率的影响因素分析.现有的文献多采用线性回归方法对该课题进行研究,但未考虑变量之间的多重共线性和采用最优变量子集建立回归模型的问题.本文采用Lasso回归方法,建立最优变量子集的回归模型对影响网络借款成功率的因素进行分析,避免了多重共线性问题对模型的干扰,同时提高了模型对数据的拟合精度.对Lending Club平台的借贷数据的实证分析结果显示,本文方法在模型的拟合精度和避免共线性方面优于对比方法.