机构侵害中小投资者违规监管博弈仿真

本文主要对股票市场中机构投资者侵害中小投资者利益这种违规行为的监管进行了博弈分析,并使用基于主体建模的动态仿真方法在Swarm仿真平台上建立了仿真模型,同时进行了仿真实验。研究指出,严厉的事前监管、完善的上市公司管理制度以及更高的监管者素质可以有效地杜绝机构投资者侵害违规行为的出现。本文通过运用经济仿真方法对股票市场具体违规行为监管问题进行研究,将股票市场监管、博弈论与经济仿真这三个研究领域结合在一起,拓展了对股票市场监管的研究手段,在经济学研究中做出了一定有益的探索。 更多还原     

基于飞机降落信息的ADS-B数据跟踪算法

在空中交通管制（ATC）领域,广域监视系统中的ADS-B接收机在飞机飞行方向改变时 ,由于其收星的数量减少导致数据率变低,并且在飞机降落过程中丢点严重。结合ADS-B数 据的特点,采用两个模型分别表示飞机的匀速运动和匀加速运动状态,利用三点速度方向预 测修正对地速度,并引入飞机降落的先验模型,实现在广域监视中对飞机的有效跟踪。 真实数据验证了该方法可有效提高数据率和改善飞机降落过程中的跟踪效果。     

一种基于遗传算法的战场频率分配方法

分析了遗传算法的原理及其在频率分配领域中的应用,提出了一种启发式战场频率 分配方法。该方法通过改进传统遗传算法的选择、交叉、变异过程来实现频率分配的特殊 用途,并借助代价函数对生成的频率分配方案进行质量评估。仿真结果表明,该方法能够在 一 定程度上提高频谱资源的使用效率,可为从事频谱管理等相关行业的技术人员提供参考。     

遗传算法在宽窄波束切换天线阵设计中的应用

采用对天线单元开关通断的方法,使天线阵形成不同的远场辐射方向图,实现阵列天 线方向图宽波束和窄波束的切换。对一个24元线阵天线阵进行了设计。提出了一种改进 的遗传算法及其目标函数模型。采用该算法对天线阵各个天线单元的电流幅度进行了优化 计算,计算结果显示能够产生满足设计要求的宽波束和窄波束方向图。最后采用HFSS软 件进行了仿真,计算结果与仿真结果吻合,证明了所提方法的有效性。     

基于最大似然估计的分集信号中频合成方法

为了降低分集信号合成时输入信号的信噪比要求,提出了一种分集信号的中频合成方法 。该方法利用最大似然估计和迭代算法,通过计算输出合成信号和输入分集信号的相关值获 得合成权值,在中频实现信号合成。仿真和实验结果表明,该方法放宽了输入信号信噪比要 高于解调捕获门限这一要求,能自动实现最大合成增益。     

数据挖掘方法在政治风险评估中的应用研究

2008年金融危机过后,中国企业将很有可能进入另一波海外收购的浪潮。然而以往的失败案例为中国企业开展海外投资敲响了警钟。基于此背景,应用K-means聚类方法,提取国家透明组织2007年CPI（Corruption Perceptions Index）数据和世界银行2007年＂良好政府＂（good government）数据,运用两次聚类方法,得出了50个存在高政治风险的国家列表。同时采用2007年的FDI对该列表进行了进一步的检验。此列表可供＂走出去＂的中国企业作为参考。     

APPLYING A GENETIC ALGORITHM TO INTERNATIONAL DIVERSIFICATION OF EQUITY PORTFOLIOS: A SOUTH AFRICAN INVESTOR PERSPECTIVE

This paper uses the genetic algorithm (GA) approach to generate a portfolio optimisation scenario of a South African investor who seeks to maximise return from investing in S&P500, FTSE100, NASDAQ, DOWJONES, CAC40 and the DAX from January 1, 2005, to January 31, 2008, but facing exchange rate risk. The GA searches for the optimal solution in the entire set of financial constraints without looking for partial derivatives of the utility function. Whereas most financial problems require a non‐linear and time‐varying model, the GA, with its survival principle of offspring chromosomes, is better suited to this type of problem than local optimisation methods. The performance of the GA is compared with two non‐linear models, namely the quadratic mean‐variance (QMV), which maximises the portfolio mean‐variance, and the quadratic variance minimisation (QVM), which minimises the portfolio variance. The results show that neither the QMV nor the QVM takes into account the domestic investors' risk attitude towards investing in foreign equities and therefore does not provide any international diversification benefits. In addition, the bootstrapping scenario of 10,000 simulations reveals that neither the QMV nor the QVM outperforms the GA in terms of Sharpe ratio and flexibility in dealing with investors' risk attitude towards investing in foreign equities denominated in foreign currencies.     

A Brief Survey of Modern Optimization for Statisticians

Modern computational statistics is turning more and more to high‐dimensional optimization to handle the deluge of big data. Once a model is formulated, its parameters can be estimated by optimization. Because model parsimony is important, models routinely include non‐differentiable penalty terms such as the lasso. This sober reality complicates minimization and maximization. Our broad survey stresses a few important principles in algorithm design. Rather than view these principles in isolation, it is more productive to mix and match them. A few well‐chosen examples illustrate this point. Algorithm derivation is also emphasized, and theory is downplayed, particularly the abstractions of the convex calculus. Thus, our survey should be useful and accessible to a broad audience.     

公开密钥算法RSA策略及程序实现

随着通信的飞速发展，信息安全显得越来越重要，计算机密码体制的基本思想就是将要保护的信息变成伪装信息，在公开密钥算法提出之前，所有密码系统的解密密钥和加密密钥彼此有着直接的联系，这也是秘密密钥的缺陷所在。为此公开密钥算法RSA算法就顺应而生。这种叫加密算法可用VB程序编程实现。     

A hybrid parallel genetic algorithm for yard crane scheduling

This paper aims at postulating a novel strategy in terms of yard crane scheduling. In this study, a dynamic scheduling model using objective programming for yard cranes is initially developed based on rolling-horizon approach. To resolve the NP-complete problem regarding the yard crane scheduling, a hybrid algorithm, which employs heuristic rules and parallel genetic algorithm (PGA), is then employed. Then a simulation model is developed for evaluating this approach. Finally, numerical experiments on a specific container terminal yard are used for system illustration. Computational results suggest that the proposed method is able to solve the problem efficiently.