A Hierarchical Ensemble Learning Framework for Energy-Efficient Automatic Train Driving

Railway transportation plays an important role in modern society. As China's massive railway transportation network continues to grow in total mileage and operation density, the energy consumption of trains becomes a serious concern. For any given route, the geographic characteristics are known a priori, but the parameters(e.g., loading and marshaling) of trains vary from one trip to another. An extensive analysis of the train operation data suggests that the control gear operation of trains is the most important factor that affects the energy consumption. Such an observation determines that the problem of energy-efficient train driving has to be addressed by considering both the geographic information and the trip parameters. However, the problem is difficult to solve due to its high dimension, nonlinearity, complex constraints, and time-varying characteristics. Faced with these difficulties, we propose an energy-efficient train control framework based on a hierarchical ensemble learning approach. Through hierarchical refinement, we learn prediction models of speed and gear. The learned models can be used to derive optimized driving operations under real-time requirements. This study uses random forest and bagging – REPTree as classification algorithm and regression algorithm, respectively. We conduct an extensive study on the potential of bagging, decision trees, random forest, and feature selection to design an effective hierarchical ensemble learning framework. The proposed framework was testified through simulation. The average energy consumption of the proposed method is over 7% lower than that of human drivers.     

基于触摸屏与PLC的龙门刨床控制改造设计

文中对西门子可编程控制器(S7-200PLC)和组态软件应用于BX2320型龙门刨床电气控制系统的改造做了介绍,对系统硬件组成和软件设计进行了阐述。技术改造后,该系统的硬件电路得到了简化,使工作台的进给速度和刨刀的进刀量直观的显示。     

Model averaging estimation for conditional volatility models with an application to stock market volatility forecast

This paper is concerned with model averaging estimation for conditional volatility models. Given a set of candidate models with different functional forms, we propose a model averaging estimator and forecast for conditional volatility, and construct the corresponding weight-choosing criterion. Under some regulatory conditions, we show that the weight selected by the criterion asymptotically minimizes the true Kullback–Leibler divergence, which is the distributional approximation error, as well as the Itakura–Saito distance, which is the distance between the true and estimated or forecast conditional volatility. Monte Carlo experiments support our newly proposed method. As for the empirical applications of our method, we investigate a total of nine major stock market indices and make a 1-day-ahead volatility forecast for each data set. Empirical results show that the model averaging forecast achieves the highest accuracy in terms of all types of loss functions in most cases, which captures the movement of the unknown true conditional volatility.     

一种基于工作流网的游戏作弊检测系统

游戏作弊对网络游戏危害很大,目前反作弊技术的瓶颈是效率低并且过多依赖于签名匹配。提出一种高效且不依赖于签名匹配的游戏作弊检测系统,用工作流网对作弊行为建模,通过流程树对作弊行为模型进行融合,在不影响检测结果的前提下节省存储空间。用热门网游的作弊软件对系统进行实验,存储空间降低率达到约60%,证明了该系统框架是可行、有效的。     

参数族λ（e^2z＋e^z）的动力学

在Ｂａｋｅｒ,Ｄｅｖａｎｅｙ研究族ｅλｚ动力系统的基础上讨论族ｆλ（ｚ）＝λ（ｅ２ｚ＋ｅｚ）的动力学问题．     

随机系统利用变结构控制方法的镇定

本文研究了Ｉｔｏ型随机系统的变结构控制,构造了参数不具有噪声激励滑动流形与变结构控制律,对Ｉｔｏ型随机系统利用变结构控制方法给出镇定控制律,并用例子演示了本文结果的应用方法。     

Morgan—Scott剖分上样条空间S6^3（Δms）的维数

众所周知,ＭｏｒｇｅｎＳｃｏｔ剖分上的样条空间的维数依赖于剖分的几何性质．本文证明了Ｄ．Ｄｉｅｎｅｒ提出的猜想对ｒ＝３是正确的．     

容器内强爆炸波的高分辨率的数值模拟

采用了自适应的非结构网格和基于有限体积法的高阶Ｇｏｄｕｎｏｖ格式对正方形、正三角形和圆形容器内中心强爆炸波的演化进行了数值模拟,着重讨论了容器壁面压力最高值发生的时间和地点以及由于Ｒａｙｌｅｉｇｈ－Ｔａｙｌｏｒ不稳定性引起的激波阵面不对称发展的过程．     

盆地古地温场演化动态数值模拟方法及其应用

盆地古地温场的演化史是盆地有机质向烃类转化以及烃类保存或变迁的决定性控制因素之一。本文从演化史的角度分析了控制盆地地温场分布的多种因素,给出了以镜质体反射率为依据的古热流反演方法原理和以热传导热对流方程为基础的古地温场的正演模拟方法及数值解法。最后给出在新疆塔里木盆地和广西十万大山盆地的应用实例。     

单回路 PID 控制系统参数整定算法的仿真研究

用计算机仿真过程控制系统ＰＩＤ调节器的工程整定法,即采用凑试法、衰减曲线法、临界比例度法和响应曲线法等,研究了改变ＰＩＤ调节器的比例（Ｐ）、积分（Ｉ）、微分（Ｄ）参数对系统过渡过程性能的影响,得到了仿真响应曲线。