基于快速流式算法的局部余弦相似属性

相似性是一种常用的衡量不同图像之间差异程度的属性,广泛应用于地震数据处理环节.由于地震数据本质上是非平稳的,局部相似性比全局相似性更适用于刻画地震数据的时-空变化特征.现有的局部相似属性可以通过正则化最小二乘问题进行计算,但是其计算过程需要大量的计算时间和数据存储空间,难以适应当前的海量数据处理任务.本文提出了一种基于快速流式算法的局部余弦相似性计算方法,其采取局部数据递推的模式,避免迭代算法带来的计算负担,在保证计算精度的前提下能够快速地表征不同数据之间的差异.流式局部余弦相似性可以用于解决不同的地震数据处理问题,包括叠前地震数据加权叠加、多波多分量数据纵横波速度比估计以及基于构造预测的断层检测,更加适用于现阶段的宽方位角和高密度采集数据的处理流程.理论模型和实际数据测试结果可以验证流式局部余弦相似性算法的效率优势和解决不同地震数据处理问题的有效性.

Internet环境三维流式传输算法研究

Internet/ Intranet环境的网络带宽和传输速率成为实现协同 CAD的瓶颈 ,针对协同 CAD的实时数据传输问题 ,本文提出了三维流式传输技术 .这种新的实时数据传输方法是与视点相关的 ,将三维几何数据分段、连续地进行传输 ,可以有效地缩短启动延时 .本文具体地研究了相关的实现算法 ,并通过实验结果证明三维流式传输可以明显地缩短启动延时 ,能够较好地满足协同

基于上下文与马尔科夫矩阵分解的流式推荐算法

为了验证用户对项目评分时所处的上下文环境是否会对用户的偏好产生影响,基于矩阵过程的马尔科夫分解方法,提出了一种基于上下文的流式推荐算法(streaming recommendation algorithm based on context,C-SRA),该方法可以从嘈杂的上下文中有效选取与评分相关的上下文信息,并将选取的上下文信息分为主观上下文和客观上下文两类。基于LDOS-CoMoDa数据集的两组对比实验显示,C-SRA算法无论是评分预测性能还是推荐性能均优于其他对比算法。

基于实时振摆监测数据的混流式机组振动区在线辨识系统

采用流式算法实时在线辨识水轮机组振动区特性曲线,诊断水轮机运行在低负荷区左边界、稳定区左边界或禁止区左边界区,在分区再分析处于正向穿越还是反向穿越。对电站合理调度和机组稳定运行提供有理论依据的指导方案,避免机组长时间处于振动区运行,可以有效提高水轮机组服役年限,减少机组故障发生,提高设备运行安全性。

HEURISTIC STUDY OF FLOWSHOP SCHEDULING TO MINIMIZE MEAN FLOW TIME WITH LOT TRANSFER CONSIDERED

Lot scheduling problem with idle time transfer between processes to minimize mean flow time is very important because to minimize mean flow time is to minimize work in process. But the problem is NP hard and no polynomial algorithm exists to guarantee optimal solution. Based the analysis the mathematical structure of the problem, the paper presents a new heuristic algorithm. Computer simulation shows that the proposed heuristic algorithm performs well in terms of both quality of solution and execution speed.

An integer multi-objective optimization model and an enhanced non-dominated sorting genetic algorithm for contraflow scheduling problem

To determine the onset and duration of contraflow evacuation, a multi-objective optimization(MOO) model is proposed to explicitly consider both the total system evacuation time and the operation cost. A solution algorithm that enhances the popular evolutionary algorithm NSGA-II is proposed to solve the model. The algorithm incorporates preliminary results as prior information and includes a meta-model as an alternative to evaluation by simulation. Numerical analysis of a case study suggests that the proposed formulation and solution algorithm are valid, and the enhanced NSGA-II outperforms the original algorithm in both convergence to the true Pareto-optimal set and solution diversity.

On Minimizing Delay with Probabilistic Splitting of Traffic Flow in Heterogeneous Wireless Networks

In the paper,we propose a framework to investigate how to effectively perform traffic flow splitting in heterogeneous wireless networks from a queue point.The average packet delay in heterogeneous wireless networks is derived in a probabilistic manner.The basic idea can be understood via treating the integrated heterogeneous wireless networks as different coupled and parallel queuing systems.The integrated network performance can approach that of one queue with maximal the multiplexing gain.For the purpose of illustrating the effectively of our proposed model,the Cellular/WLAN interworking is exploited.To minimize the average delay,a heuristic search algorithm is used to get the optimal probability of splitting traffic flow.Further,a Markov process is applied to evaluate the performance of the proposed scheme and compare with that of selecting the best network to access in terms of packet mean delay and blocking probability.Numerical results illustrate our proposed framework is effective and the flow splitting transmission can obtain more performance gain in heterogeneous wireless networks.

Fast Multi-Pattern Matching Algorithm on Compressed Network Traffic

Pattern matching is a fundamental approach to detect malicious behaviors and information over Internet, which has been gradually used in high-speed network traffic analysis. However, there is a performance bottleneck for multi-pattern matching on online compressed network traffic(CNT), this is because malicious and intrusion codes are often embedded into compressed network traffic. In this paper, we propose an online fast and multi-pattern matching algorithm on compressed network traffic(FMMCN). FMMCN employs two types of jumping, i.e. jumping during sliding window and a string jump scanning strategy to skip unnecessary compressed bytes. Moreover, FMMCN has the ability to efficiently process multiple large volume of networks such as HTTP traffic, vehicles traffic, and other Internet-based services. The experimental results show that FMMCN can ignore more than 89.5% of bytes, and its maximum speed reaches 176.470MB/s in a midrange switches device, which is faster than the current fastest algorithm ACCH by almost 73.15 MB/s.

SWFP-Miner： an efficient algorithm for mining weighted frequent pattern over data streams

Previous weighted frequent pattern （WFP） mining algorithms are not suitable for data streams for they need multiple database scans. In this paper, we present an efficient algorithm SWFP-Miner to mine weighted frequent pattern over data streams. SWFP-Miner is based on sliding window and can discover important frequent pattern from the recent data. A new refined weight definition is proposed to keep the downward closure property, and two pruning strategies are presented to prune the weighted infrequent pattern. Experimental studies are performed to evaluate the effectiveness and efficiency of SWFP-Miner.

Modelling and Predictive Control of a Buck-Boost DC-DC Converter

A predictive current control algorithm for the Buck-Boost DC-DC converter is presented in this paper. The continuous time model of the system is properly introduced, then, by imposing a proper PWM modulation pattern, its discrete time model is achieved. This last one is successfully employed in determining the steady state locus of the Buck-Boost converter, both in CCM （continuous conduction mode） and DCM （discontinuous conduction mode）. A novel continuous time equivalent circuit of the converter is introduced too, with the aim of determining a ripple free representation of the state variables of the system, over both transient and steady state operation. Then, a predictive current control algorithm, suitable in both CCM and DCM, is developed and properly checked by means of computer simulations. The corresponding results have highlighted the effectiveness of the proposed modelling and of the predictive control algorithm, both in CCM and DCM.

Detecting Communities by Revised Max-flow Method in Networks

A ubiquitous phenomenon in networks is the presence of communities within which the network connections are dense and between which they are sparser.This paper proposes a max-flow algorithm in bipartite networks to detect communities in general networks.Firstly,we construct a bipartite network in accordance with a general network and derive a revised max-flow problem in order to uncover the community structure.Then we present a local heuristic algorithm to find the optimal solution of the revised max-flow problem.This method is applied to a variety of real-world and artificial complex networks,and the partition results confirm its effectiveness and accuracy.

An implicit algorithm based on iterative modified approximate factorization method coupling with characteristic boundary conditions for solving subsonic viscous flows

An algorithm composed of an iterative modified approximate factorization(MAF(k)) method with Navier-Stokes characteristic boundary conditions(NSCBC) is proposed for solving subsonic viscous flows.A transformation on the matrix equation in MAF(k) is made in order to impose the implicit boundary conditions properly.To be in consistent with the implicit solver for the interior domain,an implicit scheme for NSCBC is formulated.The performance of the developed algorithm is investigated using spatially evolving zero pressure gradient boundary layer over a flat plate and a wall jet mixing with a cross flow over a flat plate with a square hole as the test cases.The numerical results are compared to the existing experimental datasets and a number of general correlations,together with other available numerical solutions,which demonstrate that the developed algorithm possesses promising capacity for simulating the subsonic viscous flows with large CFL number.