基于神经网络和D-S证据理论辨识两相流流型

提出一种基于电容层析成像(ECT)系统、神经网络和证据理论辨识两相流流型的方法。这种方法采用神经网络与D-S证据理论相结合的方法来辨识两相流流型,并对两相流的几种常见流型进行了辨识。仿真实验结果表明:此种方法在两相流流型辨识中具有较高的判别精度,为两相流流型辨识提供了一种有效的手段。     

A DR algorithm based on artificial potential field method

Considering player entity’s motion regularity into DR (Dead Reckoning) algorithm can improve its prediction accuracy in MMOG (Massively Multiplayer Online Games), a novel DR algorithm was proposed to solve this problem in this paper. First the artificial potential field model of player entities is created, and then the acceleration of player entities is weighted with the acceleration produced by the potential field force and the acceleration reckoned by the traditional DR algorithm. In order to calculate the weight, Q-Learning algorithm is used. The experiments show that the method can improve prediction accuracy and reduce the network traffic.     

Analysis of Internet Financial Risks Based on Deep Learning and BP Neural Network

Computational Economics - The study aims to analyze and forecast Internet financial risks based on the model based on deep learning and the Back Propagation Neural Network (BPNN). First, the theory...     

Birkhoff意义下Hojman Urrutia方程的离散变分计算

在Birkhoff框架下,采用离散变分方法研究了非Hamilton系统-Hojman-Urrutia方程的数值解法,并通过和传统的Runge-Kutta方法进行比较,说明了在Birkhoff框架下研究这类不具有简单辛结构的非Hamilton系统可以得到更可靠和精确的数值结果.     

基于信息熵多种群遗传算法的组播路由

针对网络信息不确定性和链路负载不均匀所造成的网络拥塞,提出基于信息熵的组播路由算法。该遗传算法从最小代价树开始,在多种群中不断选择信息熵较大的种群,以求得满足延时要求且路径负载较小的组播树。结果表明,该算法性能快速、有效地构造最小时延组播树,且保证网络负载均衡分布。     

IM-UFF: Extending the universal force field for interactive molecular modeling

The universal force field (UFF) is a broadly applicable classical force field that contains parameters for almost every atom type of the periodic table. This force field is non-reactive, i.e. the topology of the system under study is considered as fixed and no creation or breaking of covalent bonds is possible. This paper introduces interactive modeling-UFF (IM-UFF), an extension of UFF that combines the possibility to significantly modify molecular structures (as with reactive force fields) with a broad diversity of supported systems thanks to the universality of UFF. Such an extension lets the user easily build and edit molecular systems interactively while being guided by physics based inter-atomic forces. This approach introduces weighted atom types and weighted bonds, used to update topologies and atom parameterizations at every time step of a simulation. IM-UFF has been evaluated on a large set of benchmarks and is proposed as a self-contained implementation integrated in a new module for the SAMSON software platform for computational nanoscience available at http://www.samson-connect.net.     

相位匹配信号与混沌背景分离方法

针对混沌背景下的信号提取问题,提出了混沌噪声背景下的相位匹配噪声去除方法。它不同于以往的混沌背景下的信号提取方法,不需要相位重构对混沌进行预判估计,也不需要对信号和混沌在有限维相空间中进行几何分析。通过对混沌背景下的不同相位不同幅值的正弦信号进行分离仿真验证了本方法的有效性,通过分离度的分析表明,本方法对于弱信号的混沌背景分离效果明显,可以获得很好的去除混沌背景噪声的效果。     

无线传感器网络中一种基于覆盖的环簇路由算法

提出了一种基于覆盖的环簇路由算法CRAC。该算法利用Sink节点以广播环域坐标的方式将网络分为若干环域,并根据应用需求的服务质量计算各环域的覆盖划分以确定轮换簇,各轮换簇交替休眠以降低网络能耗。网络各环域根据能耗均衡方程确定其是否为发送环,将采集的数据并行传送到传输路径后汇聚至发送环,再由LEADER节点发送至Sink节点。仿真实验结果表明,该算法大幅度降低了网络的通信时延和能耗,延长了网络的生存时间,使节点能量均衡下降。     

嵌入式植物叶面积测量装置的研制

针对叶面积测量方法大多依赖计算机做图像处理,研制了一种嵌入式植物叶面积测量装置,以CycloneⅡ系列EP2C70F896C6为核心器件,用硬件描述语言Verilog设计叶片图像采集单元、图像存储单元、图像处理单元,内嵌NiosⅡ软核处理器完成叶面积计算。设计的关键在于解决了叶片图像实时高速采集问题,并且实现脱机运行。实验结果表明:测量装置能够测量离体叶片叶面积,适当改进,可以应用于测量叶片其他参数。