基于符号检测辅助的MMSE与LS干扰对齐算法研究

干扰对齐（IA）是一种有效消除干扰的管理机制。为了彻底消除干扰信号对期望信号的影响,通过预编码技术处理使干扰在接收端重叠,使接收端的干扰信号与期望信号有效分开。在传统最小均方误差（Minimum Mean Square Error,MMSE）算法和最小二乘（least square,LS）算法基础上,提出基于符号检测辅助的最小均方误差（Symbol Detection Aided Minimum Mean Square Error,SDA-MMSE）算法和最小二乘（Symbol Detection Aided Least Square,SDA-LS）算法。分别基于传统算法和改进算法进行迭代计算,通过仿真可看出SDA-MMSE算法的MSE较SDA-LS算法的MSE降低约20%。理论分析与仿真结果表明,改进算法较传统算法具有更好的系统性能,且SDA-MMSE算法系统性能最优。     

Bayesian Analysis of Mixture Structural Equation Models With an Unknown Number of Components

Multivariate heterogenous data with latent variables are common in many fields such as biological, medical, behavioral, and social-psychological sciences. Mixture structural equation models are multivariate techniques used to examine heterogeneous interrelationships among latent variables. In the analysis of mixture models, determination of the number of mixture components is always an important and challenging issue. This article aims to develop a full Bayesian approach with the use of reversible jump Markov chain Monte Carlo method to analyze mixture structural equation models with an unknown number of components. The proposed procedure can simultaneously and efficiently select the number of mixture components and conduct parameter estimation. Simulation studies show the satisfactory empirical performance of the method. The proposed method is applied to study risk factors of osteoporotic fractures in older people.     

基于DTMB的无源雷达在车辆定位中的应用

无源雷达系统是基于机会照射源对目标进行定位、跟踪甚至识别的系统,这种雷达系统具有先进的系统架构与算法,应用前景十分广泛。本文提出一种基于地面数字电视广播信号的无源雷达用于车辆定位与跟踪的技术。首先分析DTMB （Digital Television Terrestrial Multimedia Broadcasting）信号作为非合作照射源的优势,提出了基于DTMB信号的无源雷达目标定位与跟踪的算法,然后通过构建试验平台,实地测量数据,利用MATLAB设计实时数据处理算法对移动车辆的运动状态进行定位与跟踪。实验结果表明,利用无源雷达进行移动车辆的定位与跟踪是完全可行的。     

突发事件网络谣言危机预警及模拟仿真研究

[目的/意义] 提前进行网络谣言监控和预警是立体化防控网络谣言、增强社会稳定、提高政府执政能力的关键。移动互联网时代,突发事件发生后极易在网络上引起热点舆情、网络危机信息的传播同时为网络谣言的扩散提供良好的土壤,无形中增大了政府部门应对谣言的挑战。[方法/过程] 本文采用遗传算法优化BP神经网络构建网络谣言危机预警模型,拟实现对突发事件网络谣言的监控、预警仿真及风险的量化评估。实证分析案例选取天津"8·12"爆炸事故与"和颐酒店女生遇袭事件",通过计算机对这两起突发事件衍生的网络谣言建立预警模型,并对模拟仿真结果进行验证。[结果/结论] 结果表明,遗传算法优化BP神经网络模型在突发事件网络谣言危机预警方面具有较好的适用性,与仅采用BP神经网络模型相比预警的准确性更好。     

不正常航班恢复模型的贪婪模拟退火算法研究

为解决不正常航班恢复对航空公司带来的严重影响,研究了不正常航班恢复模型及其优化算法,对现有不正常航班恢复优化模型提出适当改进,重点设计了一种贪婪模拟退火算法。算法融合了GRASP和模拟退火算法的特点,提高了领域解的选择效率并且降低了陷入局部最优解的概率。实例证明这种算法可以处理大规模的不正常航班恢复问题,并且能够达到时间代价与结果质量的均衡。     

On the task assignment with group fairness for spatial crowdsourcing

Task assignment, the core problem of Spatial Crowdsourcing (SC), is often modeled as an optimization problem with multiple constraints, and the quality and efficiency of its solution determines how well the SC system works. Fairness is a critical aspect of task assignment that affects worker participation and satisfaction. Although the existing studies on SC have noticed the fairness problem, they mainly focus on fairness at the individual level rather than at the group level. However, differences among groups in certain attributes (e.g. race, gender, age) can easily lead to discrimination in task assignment, which triggers ethical issues and even deteriorates the quality of the SC system. Therefore, we study the problem of task assignment with group fairness for SC. According to the principle of fair budget allocation, we define a well-designed constraint that can be considered in the task assignment problem of SC systems, resulting in assignment with group fairness. We mainly consider the task assignment problem in a common One-to-One SC system (O2-SC), and our goal is to maximize the quality of the task assignment while satisfying group fairness and other constraints such as budget and spatial constraints. Specifically, we first give the formal definition of task assignment with group fairness constraint for O2-SC. Then, we prove that it is essentially an NP-hard combinatorial optimization problem. Next, we provide a novel fast algorithm with theoretical guarantees to solve it. Finally, we conduct extensive experiments using both synthetic and real datasets. The experimental results show that the proposed constraint can significantly improve the group fairness level of algorithms, even for a completely random algorithm. The results also show that our algorithm can efficiently and effectively complete the task assignment of SC systems while ensuring group fairness.     

Reviewer assignment algorithms for peer review automation: A survey

Assigning paper to suitable reviewers is of great significance to ensure the accuracy and fairness of peer review results. In the past three decades, many researchers have made a wealth of achievements on the reviewer assignment problem (RAP). In this survey, we provide a comprehensive review of the primary research achievements on reviewer assignment algorithm from 1992 to 2022. Specially, this survey first discusses the background and necessity of automatic reviewer assignment, and then systematically summarize the existing research work from three aspects, i.e., construction of candidate reviewer database, computation of matching degree between reviewers and papers, and reviewer assignment optimization algorithm, with objective comments on the advantages and disadvantages of the current algorithms. Afterwards, the evaluation metrics and datasets of reviewer assignment algorithm are summarized. To conclude, we prospect the potential research directions of RAP. Since there are few comprehensive survey papers on reviewer assignment algorithm in the past ten years, this survey can serve as a valuable reference for the related researchers and peer review organizers.     

MINRES法和有限元法解奇摄动反应扩散方程

讨论奇摄动反应扩散方程 的数值逼近求解问题, 及 均为正实数. 利用有限元方法并结合最小残量法, 给出求解该问题的一个新方 法, 该方法修正了单纯采用有限元方法求解时在边界附近呈现出的非正常扰动的 现象, 避免了因为 过小所引起的解的变异, 从而得到更加精确的数值结果.     

基于遗传算法的高校排课系统设计与实现

随着高等教育的发展,学生人数不断增加,而教室资源和教师资源有可能相对有限,排课就成为教学管理中十分重要且又相当繁重的工作之一。文章根据高校排课特点,在对排课系统及遗传算法基本理论分析的基础上,使用基本遗传算法SGA,设计并开发出了一个基于B/S模式的排课系统CAS,以满足高校教学管理工作不断发展的需要。     

非结构化数据分类整合在贵州项目网中的设计与实现

针对贵州项目网中非结构数据量大的特点和不易管理的问题,文章采用了基于遗传算法分类的方法和数据库管理的方法对贵州项目网进行了数据管理的重构设计并在贵州项目网建设中得以实践。结果表明基于遗传算法分类与数据库管理适用于整合管理大量的非结构数据。