Two methods for sensitivity analysis of coagulation processes in population balances by a Monte Carlo method

We consider two stochastic simulation algorithms for the calculation of parametric derivatives of solutions of a population balance equation, namely, forward and adjoint sensitivity methods. The dispersed system is approximated by an N-particle stochastic weighted ensemble. The infinitesimal deviations of the solution are accounted for through infinitesimal deviation of the statistical weights that are recalculated at each coagulation. In the forward method these deviations of the statistical weights immediately give parametric derivatives of the solution. In the second method the deviations of the statistical weights are used to calculate a finite-mode approximation of the linearized version of the population balance equation. The linearized equation allows for the calculation of the eigenmodes and eigenvalues of the process, while the parametric derivatives of the solution are given by a Lagrange formalism.     

A probabilistic simulator for population dynamics of quasispecies

We constructed a probabilistic simulator that allows all the events in population dynamics such as death, birth, mutation, and suppression/stimulation to be described by probabilistic rules. The simulator also facilitates a lattice used for expressing distribution and diversity (number of distinct strains) of quasispecies. The simulator is used to investigate the diversity threshold in HIV and T-cell interaction. This work was presented in part at the 13th International Symposium on Artificial Life and Robotics, Oita, Japan, January 31–February 2, 2008     

Efficient solution of population balance equations with discontinuities by finite elements

Two refinements of Galerkin's method on finite elements were evaluated for the solution of population balance equations for precipitation systems. The traditional drawbacks of this approach have been the time required for computation of the two-dimensional integrals arising from the aggregation integrals and the difficulty in handling discontinuities that often arise in simulations of seeded reactors. The careful arrangement of invariant integrals for separable aggregation models allows for a thousandfold reduction in the computational costs. Discontinuities that may be present due to the hyperbolic nature of the system may be specifically tracked by the method of characteristics. These discontinuities will arise only from the initial distribution or nucleation and are readily identified. A combination of these techniques can be used that is intermediate in computational cost while still allowing discontinuous number densities. In a case study of calcium carbonate precipitation, it is found that the accuracy improvement gained by tracking the slope discontinuity may not be significant and that the computation speed may be sufficient for dynamic online optimization.     

采用时间差分算法的九路围棋机器博弈系统

围棋机器博弈是机器博弈中重要的分支之一,其庞大的博弈空间给机器博弈研究者带来了巨大挑战.目前围棋机器博弈多采用静态估值搜索与蒙特卡洛树搜索,故将时间差分算法引入至九路围棋机器博弈系统中,提出基于时间差分算法的围棋机器博弈系统模型,该博弈系统具有一定的自学习能力,能在不断的对弈中逐步提高博弈能力.通过与采用α-β搜索算法的博弈系统进行实际对弈,证明了该方法的可行性.     

面向动态任务合作求解的联盟模型

多Agent系统中,Agent间通过形成联盟达到提高任务求解能力,获取更多收益的目的。主要关注联盟模型的改进和联盟形成阶段的改进,基于ARG(agent,role,group)元模型和学习机制提出了一种采用角色和学习机制的新联盟模型CLAR(coalition model based on learnin gagent and role);在采用合同网协议的CLAR联盟模型中提出了两阶段联盟形成机制;通过捕食者问题实验验证了角色和学习机制的作用,以及两阶段联盟形成机制在减少通讯代价上的作用。     

图像识别技术在3D-RPG游戏开发中的应用

基于OGRE(Object-oriented Graphics Rendering Engine)设计开发一个3D-RPG(Role-Playing Game)游戏引擎RPGGE(RPG Game Engine)。在RPGGE中融入图像识别技术,使玩家可以通过摄像头识别手势来增加游戏交互。RPGGE开发包括渲染系统、输入输出系统、声音系统、识别系统。     

用于多峰函数优化的小生境差分演化算法

针对监控视频图像的特点,提出了一种有效的实时视频降噪算法。首先结合多帧图像采用基于Non—localmeans的运动检测方法自适应地区分图像的运动区域和静止区域,对静止区域采用时域加权均值滤波,对运动区域采用空域ANL滤波。充分利用了视频的时域、空域信息,在去除视频序列噪声的同时很好地保护了图像的细节。实验结果表明,提出的算法在不造成运动拖影的前提下,能够显著提高视频的信噪比和图像的主观质量。     

基于Moran过程的竞争性舆情信息的网络传播博弈模型

新的媒体环境下,在享受不同形式在线社交网络提供便捷信息互动渠道的同时,需要加强对信息传播的管理与引导,防止其发展成为负面舆情信息肆意滋生的温床。结合传统演化博弈论与复杂网络理论,提出了竞争性舆情信息的网络传播博弈模型,并理论分析了正面舆情信息传播占优的收益条件及群体规模;随后,结合实际案例,通过仿真实验对比分析三种博弈环境下网络舆情的演化特征。三种博弈环境下,正面舆情信息传播策略占优条件均与收益有关,弱选择情境对收益参数的要求最为严格;强、弱选择情景下策略占优的条件还与群体规模有关,且强选择情景对群体规模的要求更为严格。