厦门市城市空间结构分布的自组织特征

基于地理信息系统空间分析模块,对2002年TM遥感图像的综合分析,以及对厦门市地质地貌、植被、城镇分布和社会经济文化的充分研究,指出了厦门市生态空间结构的自组织特征,厦门市由海岛型城市向海湾型城市演进过程中所遵循的自组织规律及城市规划方向.     

基于GIS技术的学生体质评价系统构建

以软件技术和空间信息处理为核心的GIS技术数据为平台,利用它的开发函数库二次开发出专用的学生体质评价地理信息系统软件,得到相关的空间分析结果.多角度的分析学生体质数据内在价值,预测今后学生体质的发展趋势,并提出相应的建议.     

无线传感器网络多目标路由的改进蚁群算法

提出一种集能耗、时延、鲁棒性和传输效率等于一体的多目标路由,且各目标的权重可以根据实际情况进行调节,具有较强的灵活性,提出一种正反馈和负反馈并存机制的蚁群算法,其主要思想是,若前路径比以往求得的最好路径性能更优,则当前路径信息素将加强,同时用当前路径取代最好路径,否则当前路径信息素减弱.用该改进的蚁群算法求解无线传感器网络多目标路由问题,实验数据表明:改进的蚁群算法的路由各方面性能良好,并优于目前其他典型路由.     

二维具时滞Hopfield神经网络动力学行为研究

Hopfield神经网络模型是对人脑神经网络的某些机理与机制的抽象,它可以模拟大脑实现联想记忆和优化计算等方面的功能.本文对一类二维具时滞的Hopfield神经网络模型进行了理论分析,给出了系统可能出现的稳定平衡点、周期解以及混沌奇异吸引子的参数选取信息,并在理论分析的基础上进行了数值模拟,用计算机描绘出解曲线图.本结果对人工神经网络的应用提供参数依据.     

平面束的应用及其注记

将空间点到直线的距离和2条异面直线间的距离转化为点到过直线的平面束距离的最大值,给出了计算公式,并讨论了应用平面束方程的一点注记。     

Online Distributed Fault Detection of Sensor Measurements

In wireless sensor networks (WSNs), a faulty sensor may produce incorrect data and transmit them to the other sensors. This would consume the limited energy and bandwidth of WSNs. Furthermore, the base station may make inappropriate decisions when it receives the incorrect data sent by the faulty sensors. To solve these problems, this paper develops an online distributed algorithm to detect such faults by exploring the weighted majority vote scheme. Considering the spatial correlations in WSNs, a faulty sensor can diagnose itself through utilizing the spatial and time information provided by its neighbor sensors. Simulation results show that even when as many as 30% of the sensors are faulty, over 95% of faults can be correctly detected with our algorithm. These results indicate that the proposed algorithm has excellent performance in detecting fault of sensor measurements in WSNs.     

On Peer-Assisted Data Dissemination in Data Center Networks: Analysis and Implementation简

Data Center Networks （DCNs） are the fundamental infrastructure for cloud computing. Driven by the massive parallel computing tasks in cloud computing, one-to-many data dissemination becomes one of the most important traffic patterns in DCNs. Many architectures and protocols are proposed to meet this demand. However, these proposals either require complicated configurations on switches and servers, or cannot deliver an optimal performance. In this paper, we propose the peer-assisted data dissemination for DCNs. This approach utilizes the rich physical connections with high bandwidths and mutli-path connections, to facilitate efficient one-to-many data dissemination. We prove that an optimal P2P data dissemination schedule exists for FatTree, a specially- designed DCN architecture. We then present a theoretical analysis of this algorithm in the general multi-rooted tree topology, a widely-used DCN architecture. Additionally, we explore the performance of an intuitive line structure for data dissemination. Our analysis and experimental results prove that this simple structure is able to produce a comparable performance to the optimal algorithm. Since DCN applications heavily rely on virtualization to achieve optimal resource sharing, we present a general implementation method for the proposed algorithms, which aims to mitigate the impact of the potentially-high churn rate of the virtual machines.     

汽轮机故障诊断中的信息熵融合

在汽轮机轴系振动故障模拟试验的基础上,对大量故障模拟试验数据进行计算,建立了典型故障的4种信息熵样本.采用概率神经网络对故障信号的4种信息熵特征进行融合研究,并将融合结果与最小距离分类器的分类效果进行了对照分析.研究表明,概率神经网络可实现对训练样本100%的正确识别率,对"陌生"样本的正确识别率也超过80%,其识别效果远远超过最小距离分类器.可见,概率神经网络综合了贝叶斯分类器和神经网络的优势,在汽轮机故障模式分类方面具有明显的优势,利用概率神经网络融合信号的信息熵特征实现汽轮机轴系故障模式识别是一种可行有效的方法.     

Reliable and Energy Efficient Target Coverage for Wireless Sensor Networks

A critical aspect of applications with Wireless Sensor Networks (WSNs) is network lifetime.Power-constrained WSNs are usable as long as they can communicate sense data to a processing node.Poor communication links and hazardous environments make the WSNs unreliable.Existing schemes assume that the state of a sensor covering targets is binary:success (covers the targets) or failure (cannot cover the targets).However,in real WSNs,a sensor covers targets with a certain probability.To improve WSNs’ reliability,we should consider that a sensor covers targets with users’ satisfied probability.To solve this problem,this paper first introduces a failure probability into the target coverage problem to improve and control the system reliability.Furthermore,we model the solution as the α-Reliable Maximum Sensor Covers (α-RMSC) problem and design a heuristic greedy algorithm that efficiently computes the maximal number of α-Reliable sensor covers.To efficiently extend the WSNs lifetime with users’ pre-defined failure probability requirements,only the sensors from the current active sensor cover are responsible for monitoring all targets,while all other sensors are in a low-energy sleep mode.Simulation results validate the performance of this algorithm,in which users can precisely control the system reliability without sacrificing much energy consumption.     

Banach空间中含H-增生算子的广义集值拟变分包含的迭代算法

引入和研究了Banach空间中含H-增生算子的广义集值拟变分包含.利用H-增生算子生成的预解算子,给出了一类广义集值拟变分包含的迭代算法,并证明了该迭代算法的强收敛性.文中所得到的结果改进和推广了文献[7-10]中的相关结果.