基于BP算法的企业经营状况评价模型

利用2008年的64家公司的数据构建了以每股收益、每股净资产、净资产收益率、主营利润增长率为主的企业经营状况的指标体系,并通过matlab软件建立了基于BP算法的企业经营状况的评价模型。最后利用该模型对2009年的17家公司的经营状况进行了评价,仿真结果表明,基于BP算法的企业经营状况评价模型是一种非常有效的评价方法。     

静态分簇下的大规模分布式天线系统用户调度算法

在大规模分布式天线系统中,静态分簇和用户调度带来的簇间干扰问题会导致系统和速率下降。针对这个问题,提出了一种两阶段贪婪用户调度算法。首先,每个簇内并行实施贪婪用户调度;然后,从全局上再次利用贪婪算法来剔除簇间干扰较大、服务质量较差的用户,使得系统和速率进一步提升。仿真结果表明,随着不同系统参数的改变,两阶段贪婪用户调度算法可有效提高系统和速率。     

基于DRAGAN的通信信号波形生成技术

为了解决非合作通信情况下,具有特定帧结构的复杂信号难以重构问题,设计了一种利用深度无悔分析生成对抗网络(deep regret analytic generative adversarial networks,DRAGAN)重构信号的方法.首先利用无悔算法(no-regret algorithms)对判别器损失函数进行...     

A novel differential evolution algorithm for joint replenishment problem under interdependence and its application

In this paper, we propose a new differential evolution (DE) algorithm for joint replenishment of inventory using both direct grouping and indirect grouping which allows for the interdependence of minor ordering costs. Since solutions to the joint replenishment problem (JRP) can be represented by integer decision variables, this makes the JRP a good candidate for the DE algorithm. The results of testing randomly generated problems in contrastive numerical examples and two extended experiments show that the DE algorithm provides close to optimal results for some problems than the evolutionary algorithm (EA), which has been proved to be an efficient algorithm. Moreover, the DE algorithm is faster than the EA for most problems. We also conducted a case study and application results suggest that the proposed model is successful in decreasing total costs of maintenance materials inventories significantly in two power companies.     

A continuous time model for multiple yard crane scheduling with last minute job arrivals

Container terminal (CT) operations are often bottlenecked by slow YC (yard crane) movements. Efficient YC scheduling to reduce the PM waiting time is therefore critical in increasing a CT's throughput. This paper develops an efficient continuous time MILP model for YC scheduling. The model treats realistic operational constraints such as multiple inter-crane interference, fixed YC separation distances, simultaneous container storage/retrievals, realistic YC acceleration/deceleration stages and gantry time, and require far fewer integer variables than previous work. The model significantly improves the solution quality compared to the existing discrete time models and other heuristics found in the literature. Using heuristics and a rolling-horizon algorithm, our model can solve actual container yard (CY) problems quickly and robustly in polynomial time. Also, to cope with the last minute container arrivals which can disrupt routine CT operations, two methods for handling these last minute job insertions are discussed and compared.     

多道程序设计中死锁的产生和解决

在多道程序系统中,通过多进程并发执行可提高系统资源利用率和系统的处理能力,但也带来了风险,死锁现象。本文讨论了多道程序设计中死锁的起因以及解决方法。     

基于模糊关联规则在电子商务数据挖掘中的研究

数据挖掘是一种新兴的信息处理技术,它通过对商业数据的分析处理,可以发现蕴藏在数据中的商业知识,挖掘数据内在的联系、规则和模式,辅助商业决策。在电子商务环境下的数据挖掘的研究,主要是进行客户访问信息的挖掘．文章在考虑了数据来源之后,简要介绍数据预处理过程．最后给出了模糊集与传统的关联规则挖掘结合的算法。     

基于遗传算法的毫米波大规模MIMO系统混合预编码

目前混合预编码方案中,大多采取高精度的移相器作为模拟预编码的设计基础,使得系统成本增加。针对这一问题,探讨了有限精度射频前端的混合预编码设计。为了实现更高的频谱利用率,考虑到天线权值的最优组合为一NP（Non-deterministic Polynomial）问题,受机器学习启发,采用遗传算法对阵列中阵元的相位取值进行建模设计模拟预编码。通过信道矩阵与模拟预编码矩阵的乘积引入等效信道矩阵,考虑用户间干扰,以最大信干噪比准则进行数字预编码设计。仿真结果表明,该方案得到的混合预编码矩阵其系统性能可逼近全数字预编码矩阵的性能。     

应急物流配送问题的蚁群聚类算法研究

提出了一种用于解决突发事件下,物流配送多目标优化问题的蚁群聚类优化算法。突发事件下的物流配送规划一般包含两方面内容,将救灾物资运往受灾地区和将灾区的伤员及时送至各医疗点。将多目标问题转化为单目标问题,结合蚁群的墓地构造行为特点,利用改进LF蚁群聚类模型,以节点需求未得到满足的不满意度最小和路由时间最短为优化目标,用LF蚁群聚类方法按约束条件进行聚类,最终确定车辆路由线路。     

Efficient Universal Portfolios for Past-Dependent Target Classes

We present a new universal portfolio algorithm that achieves almost the same level of wealth as could be achieved by knowing stock prices ahead of time. Specifically the algorithm tracks the best in hindsight wealth achievable within target classes of linearly parameterized portfolio sequences. The target classes considered are more general than the standard constant rebalanced portfolio class and permit portfolio sequences to exhibit a continuous form of dependence on past prices or other side information. A primary advantage of the algorithm is that it is easily computable in a polynomial number of steps by way of simple closed-form expressions. This provides an edge over other universal algorithms that require both an exponential number of computations and numerical approximation.