基于Kriging模型的多点加点准则和并行代理优化算法

针对并行仿真环境下复杂工程系统的优化设计问题,提出一种基于Kriging模型、多目标策略和聚类方法的并行代理优化算法.该算法的多点加点准则,以同时优化期望改进准则和可行性概率准则为目标,首先生成兼具目标响应改进和可行域边界刻画功能的备选试验点集;再利用聚类方法从备选点集中选取多个有代表性的新试验点.通过两个数值算例和一个工程算例,将所提并行优化算法与已有算法做比较,结果表明所提算法具有更高的优化精度、效率和稳健性.     

鲸鱼优化相关向量机的网络控制系统变采样周期调度

针对资源受限的网络控制系统,提出一种基于鲸鱼优化相关向量机的变采样周期调度算法。通过网络监测模块获取网络带宽与数据传输时间数据,建立鲸鱼优化相关向量机的预测模型,实现对网络带宽及数据传输时间的预测。采用模糊推理计算系统各回路通信带宽的分配权重,进而结合通信带宽及数据传输时间的预测值对各闭环回路的采样周期进行计算,完成采样周期的实时调节。仿真结果表明,在资源受限条件下,所提算法保证了系统的稳定性与控制精度。     

Compressive sensing based multiuser detector for massive MBM MIMO uplink

Media based modulation(MBM)is expected to be a prominent modulation scheme,which has access to the high data rate by using radio frequency(RF)mirrors and fewer transmit antennas.Associated with multiuser multiple input multiple output(MIMO),the MBM scheme achieves better performance than other conventional multiuser MIMO schemes.In this paper,the massive MIMO uplink is considered and a conjunctive MBM transmission scheme for each user is employed.This conjunctive MBM transmission scheme gathers aggregate MBM signals in multiple continuous time slots,which exploits the structured sparsity of these aggregate MBM signals.Under this kind of scenario,a multiuser detector with low complexity based on the compressive sensing(CS)theory to gain better detection performance is proposed.This detector is developed from the greedy sparse recovery technique compressive sampling matching pursuit(CoSaMP)and exploits not only the inherently distributed sparsity of MBM signals but also the structured sparsity of multiple aggregate MBM signals.By exploiting these sparsity,the proposed CoSaMP based multiuser detector achieves reliable detection with low complexity.Simulation results demonstrate that the proposed CoSaMP based multiuser detector achieves better detection performance compared with the conventional methods.     

多精英采样与个体差分学习的分布估计算法

提出了基于多精英采样和差分搜索的分布估计算法EDA-M/D (Estimation distribution algorithm based on multiple elites sampling and individuals differential search)。EDA-M/D利用多精英个体独立采样生成子代来提升算法全局搜索能力,利用精英群体分布的σ²约束采样半径,实现种群从全局搜索逐步过度到局部搜索。当精英群体停滞时,劣势个体借助精英群体的μ和种群历史最优解进行差分搜索,帮助种群跳出局部最优解。通过多精英采样与差分搜索的自适应协同实现种群宏观信息与个体微观信息的有机融合。实验结果表明EDA-M/D在稳定性和搜索能力方面均表现出明显的优势。     

供应链产品质量检查策略的比较研究

研究由一个供应商和一个零售商组成的供应链,建立存在质量不确定与检查错误下的报童模型,比较分析全检、抽检、分批抽检以及组合策略在分散式与集中式供应链中对零售商订购决策与质量控制效率的影响.结果表明,次品率的增加会降低零售商订购产品的动因,但会增加组合策略下零售商的订购量与利润,同时对集中式供应链中全检策略下的零售商有利;比较策略可知,在分散式供应链中,若次品率较低,则分批抽检策略最优,而随着次品率的提高,组合策略会更优,而在集中式供应链中,全检策略最优;此外零售商质量控制策略的选择受到检查精度、责任成本、次品率阈值、抽检数量以及分批次数等诸多因素的影响,最优策略不尽相同,但不会改变零售商利润随次品率变化的趋势.     

基于RTCP的流媒体服务器速率动态适配研究

研究并实现了一种基于实时流控制协议RTCP的流媒体发送速率适配方法,通过接收RTCP RR包及RTCP NADU包得到关键控制参数--丢包率、抖动、空闲缓冲区大小,对这些参数设置阈值来决定服务器端发送速率的切换方向,切换后的发送速率则通过决策器对估算的网络带宽与根据控制参数调整的发送速率相运算得到.实践证明:本方法具有抗振荡性、带宽预测性、能快速响应网络状况变化、有效控制缓冲区上溢或下溢的优点.     

Optimal sampling frequency for volatility forecast models for the Indian stock markets

This paper evaluates the performance of conditional variance models using high‐frequency data of the National Stock Index (S&P CNX NIFTY) and attempts to determine the optimal sampling frequency for the best daily volatility forecast. A linear combination of the realized volatilities calculated at two different frequencies is used as benchmark to evaluate the volatility forecasting ability of the conditional variance models (GARCH (1, 1)) at different sampling frequencies. From the analysis, it is found that sampling at 30 minutes gives the best forecast for daily volatility. The forecasting ability of these models is deteriorated, however, by the non‐normal property of mean adjusted returns, which is an assumption in conditional variance models. Nevertheless, the optimum frequency remained the same even in the case of different models (EGARCH and PARCH) and different error distribution (generalized error distribution, GED) where the error is reduced to a certain extent by incorporating the asymmetric effect on volatility. Our analysis also suggests that GARCH models with GED innovations or EGRACH and PARCH models would give better estimates of volatility with lower forecast error estimates. Copyright © 2008 John Wiley & Sons, Ltd.     

Taming theory with thought experiments: Understanding and scientific progress

I claim that one way thought experiments contribute to scientific progress is by increasing scientific understanding. Understanding does not have a currently accepted characterization in the philosophical literature, but I argue that we already have ways to test for it. For instance, current pedagogical practice often requires that students demonstrate being in either or both of the following two states: 1) Having grasped the meaning of some relevant theory, concept, law or model, 2) Being able to apply that theory, concept, law or model fruitfully to new instances. Three thought experiments are presented which have been important historically in helping us pass these tests, and two others that cause us to fail. Then I use this operationalization of understanding to clarify the relationships between scientific thought experiments, the understanding they produce, and the progress they enable. I conclude that while no specific instance of understanding (thus conceived) is necessary for scientific progress, understanding in general is.     

预期短缺ES估计的稳定性分析

在风险管理中,风险量度估计的稳定性对金融机构的经济资本确定及风险分配起着重要的作用.本文从预期短缺(ESα)估计的稳定性角度分析重要性抽样技术和Monte Carlo模拟在估计信用资产组合ESα方面的差异.结果表明,由于组合损失分布尾部事件的稀有性,与传统的Monte Carlo模拟方法相比,运用重要性抽样方法估计的ESα比较稳定,且生成的风险贡献能够明显地体现出资产间不同的风险特征.     

分布式虚拟环境中时间一致性研究

在分布式虚拟环境中,为了给用户造成逼真的和符合真实世界的时空感受,需要解决时空不一致的问题。要做到时空一致,时间一致是关键,本文主要对分布式虚拟环境中时间一致性进行了研究,介绍了几种时间同步的方案,并结合实际应用,给出了实验的结论。