Likelihood-based approaches for multivariate linear models under inequality constraints for incomplete data

In this paper, we consider a multivariate linear model with complete/incomplete data, where the regression coefficients are subject to a set of linear inequality restrictions. We first develop an expectation/conditional maximization (ECM) algorithm for calculating restricted maximum likelihood estimates of parameters of interest. We then establish the corresponding convergence properties for the proposed ECM algorithm. Applications to growth curve models and linear mixed models are presented. Confidence interval construction via the double-bootstrap method is provided. Some simulation studies are performed and a real example is used to illustrate the proposed methods.     

基于VB与Matlab COM的模糊算法研究

本文利用Matlab COM Builder技术将Matlab的模糊算法打包发给VB,实现在VB中调用Mat-lab函数文件,使其完全脱离Matlab环境,为其进一步在组态软件中实现智能控制策略及控制系统在线仿真奠定基础。     

间接光滑逼近

改进了链接超平面模型，并在找链接算法的基础上给出了一个处处光滑的间接光滑逼近算法，该算法在保持找链接算法简洁这一优势的同时，给出了处处光滑的逼近结果，且这一算法可以用于任意维空间。     

基于任务跟踪的在线租赁问题与竞争策略研究

现实经济活动中,有许多租赁融资决策既非纯在线租赁问题也非纯离线租赁问题,而是介于二者之间的具有部分已知信息的在线租赁问题.基于此研究了工作任务总量已知而工作任务进展序列未知的在线设备租赁问题,以租赁工作所需设备的费用最小为优化目标,建立了该问题的基本数学模型,提出了任务跟踪策略,给出并证明了基于这一策略的算法的竞争比.最后,把该在线租赁问题的竞争比与经典的在线租赁问题的竞争比做了比较分析,结果表明在线租赁问题的算法优于经典的在线算法,竞争性能得到了较大的提高.     

有时间窗车辆路径问题的模型及其改进模拟退火算法研究

论文在对有时间窗车辆路径问题进行描述的基础上,建立了该问题的基于直观描述的数学模型.论文还根据有时间窗车辆路径问题的特点构造了求解该问题的改进模拟退火算法,并进行了实验计算.计算结果表明,用本文设计的改进模拟退火算法求解有时间窗车辆路径问题,不仅可以取得很好的计算结果,而且算法的计算效率较高,收敛速度较快,计算结果也较稳定.     

有模糊时间窗的车辆调度组合干扰管理研究

研究带有模糊时间窗的车辆调度组合干扰管理模型及其混合遗传算法.采用时间窗模糊化处理方法,定义客户满意度函数,根据干扰管理思想对车辆调度中组合性干扰事件进行分析,从配送路径、配送成本和客户满意度三个方面进行干扰辨识与度量,建立基于模糊时间窗的车辆调度组合干扰管理模型;构造模型求解的混合遗传算法,将最佳客户插入规则与遗传算法结合,同时在算法中嵌入模糊优化程序以处理问题的模糊特征;进行数值实验,实验结果验证了模型与算法的有效性.     

论类ChatGPT通用人工智能治理——基于算法安全审查视角

类ChatGPT具有潜意识形态性,其引入和嵌入应用易招致非传统国家安全威胁。类ChatGPT通用人工智能算法受资本与西方价值观的浸润,冲击国家意识形态安全和情报安全,易诱发意识形态安全风险,并为网络情报的获取和传输提供诸多便利条件;杜撰假舆论,致使社会谣言泛滥,或将挑战社会公共安全;收集存储处理用户数据,严重威胁国家数据安全;阻碍发展中国家崛起的步伐,使产业跨国转移变得缺乏现实意义并重新定义社会人力资源成本上限,或将挟制他国经济发展安全。我国算法审查制度面临专门审查主体缺失、审查范围不明和审查法律规范体系化水平严重滞后等现实问题。应当以总体国家安全观为指引,明确中央科技委员会领导的、国务院数据安全局负责执行的算法安全专门审查主体机制,统筹算法审查宏观设计;充分发挥平台经营者和使用者的协同共治效能,夯实算法审查的社会基础;将算法文化监控、算法可解释性和算法可控性纳入算法审查范围,合理评估算法对国家和社会的冲击,明确算法安全内容;制定“算法安全法”以破解政策敏锐立法滞后的困局,回应算法安全制度的现实需求和总体国家安全的需要,提升国家在科技领域的监管能力,积极应对西方国家算法霸权,加速推进类ChatGPT通用人工智能本土化应用及国产化替代进程。     

Simultaneous Bayesian modeling of longitudinal and survival data in breast cancer patients

Abstract

Using simultaneous Bayesian modeling, an attempt is made to analyze data on the size of lymphedema occurring in the arms of breast cancer patients after breast cancer surgery (as the longitudinal data) and the time interval for disease progression (as the time-to-event occurrence). A model based on a multivariate skew t distribution is shown to provide the best fit. This outcome was confirmed by simulation studies too.     

基于CatBoost算法的P2P违约预测模型应用研究

在互联网金融背景下,智能算法的应用能够为经济领域提供新的思路和方向,有效推动中国互联网金融向“互联网+金融+智能”模式的转变。P2P网络借贷是通过P2P公司搭建的第三方互联网平台进行“个人对个人”的直接信贷。以人人贷平台为研究对象,运用特征工程技术,将CatBoost算法应用于构建P2P违约预测模型,并对违约影响因素进行综合分析。结果表明,CatBoost算法的预测准确率达96%,对实际结果的拟合效果较好,并能够对模型出错所导致的损失成本进行有效控制。此外,综合分析违约影响因素发现,借款人的信用情况对借款人违约行为影响较大,其中还清贷款次数、逾期次数与成功借款次数应作为借款人信用评估的重要参考指标。结合本文的研究成果与中国P2P行业发展状况,本文建议P2P平台积极促进数据分析与测算分析技术的革新与应用,政府及相关部门形成政策法规的同步发展,促成从平台内部到外部环境的合力发展态势。     

Performance characteristics of the adjusted r2 algorithm for determining the start of the terminal disposition phase and comparison with a simple r2 algorithm and a visual inspection method

The adjusted r² algorithm is a popular automated method for selecting the start time of the terminal disposition phase (t_z) when conducting a noncompartmental pharmacokinetic data analysis. Using simulated data, the performance of the algorithm was assessed in relation to the ratio of the slopes of the preterminal and terminal disposition phases, the point of intercept of the terminal disposition phase with the preterminal disposition phase, the length of the terminal disposition phase captured in the concentration‐time profile, the number of data points present in the terminal disposition phase, and the level of variability in concentration measurement. The adjusted r² algorithm was unable to identify t_z accurately when there were more than three data points present in a profile's terminal disposition phase. The terminal disposition phase rate constant (λ_z) calculated based on the value of t_z selected by the algorithm had a positive bias in all simulation data conditions. Tolerable levels of bias (median bias less than 5%) were achieved under conditions of low measurement variability. When measurement variability was high, tolerable levels of bias were attained only when the terminal phase time span was 4 multiples of t_1/2 or longer. A comparison of the performance of the adjusted r² algorithm, a simple r² algorithm, and t_z selection by visual inspection was conducted using a subset of the simulation data. In the comparison, the simple r² algorithm performed as well as the adjusted r² algorithm and the visual inspection method outperformed both algorithms. Recommendations concerning the use of the various t_z selection methods are presented.