A Progressive Deployment Strategy for Cooperative Adaptive Cruise Control to Improve Trafc Dynamics

Cooperative adaptive cruise control(CACC)vehicles are intelligent vehicles that use vehicular ad hoc networks(VANETs)to share trafc information in real time.Previous studies have shown that CACC could have an impact on increasing highway capacities at high market penetration.Since reaching a high CACC market penetration level is not occurring in the near future,this study presents a progressive deployment approach that demonstrates to have a great potential of reducing trafc congestions at low CACC penetration levels.Using a previously developed microscopic trafc simulation model of a freeway with an on-ramp—created to induce perturbations and trigger stop-and-go trafc,the CACC system s efect on the trafc performance is studied.The results show signifcance and indicate the potential of CACC systems to improve trafc characteristics which can be used to reduce trafc congestion.The study shows that the impact of CACC is positive and not only limited to a high market penetration.By giving CACC vehicles priority access to high-occupancy vehicle(HOV)lanes,the highway capacity could be signifcantly improved with a CACC penetration as low as 20%.     

An intelligent stock trading system using comprehensive features

The aim of this study is to predict automatic trading decisions in stock markets. Comprehensive features (CF) for predicting future trend are very difficult to generate in a complex environment, especially in stock markets. According to related work, the relevant stock information can help investors formulate objects that may result in better profits. With this in mind, we present a framework of an intelligent stock trading system using comprehensive features (ISTSCF) to predict future stock trading decisions. The ISTSCF consists of stock information extraction, prediction model learning and stock trading decision. We apply three different methods to generate comprehensive features, including sentiment analysis (SA) that provides sensitive market events from stock news articles for sentiment indices (SI), technical analysis (TA) that yields effective trading rules based on trading information on the stock exchange for technical indices (TI), as well as the trend-based segmentation method (TBSM) that raises trading decisions from stock price for trading signals (TS). Experiments on the Taiwan stock market show that the results of employing comprehensive features are significantly better than traditional methods using numeric features alone (without textual sentiment features).     

ITS无线接入网业务建模和调度方法设计

首先介绍了面向智能交通系统(Intelligent Transportation System,ITS)的无线接入网网络结构和主要业务,对车路协同业务和PTT语音业务进行了分析和建模。然后根据不同业务的特点及QoS需求提出具有针对性的调度方案:对于车路协同业务,采用适应车速的动态调度方法;对于PTT语音业务,采用基于状态转换的调度方法;对于视频和其他对时延不敏感的数据业务,采用缓存请求的调度方式。最后在OPNET平台上对调度方法进行仿真,针对各种ITS业务得出延时、丢包率等性能曲线,验证了算法的有效性,这也为ITS接入网的网络设计提供了参考。     

改进贝叶斯分类的智能短信分类方法

随着移动通信技术的不断发展,手机的普及率在不断上升,而短信作为传统的移动通信服务,长久以来一直在人们的日常生活中占据着极为重要的位置。可以说,短信在一定程度上记录了人们生活的轨迹。但是,现有的短信管理系统仅对短信进行以联系人为特征分类、以时间为顺序显示的简单非智能化的管理,导致了用户手机中各类短信混杂不清,短信的管理效率极低。通过研究短信的特征,分析传统的基于文档频率的特征值提取方法和基于互信息的特征值提取方法的优势与不足,提出了一种适用于短信的基于词频和互信息的特征值提取方法,并结合短信长度实现了一种改进的贝叶斯分类算法。实验证明,算法在进行短信分类时可以得到相当可观的召回率和准确率。     

复杂光照下的缩微道路车道线检测方法

为了解决复杂光照下的缩微道路车道线检测问题,提出了一种适用于复杂光照下的缩微道路车道线检测方法。首先运用朴素贝叶斯对不同光照下的车道图像进行分类,然后对分类后的车道图像采取相应的图像处理方法,最后运用改进的大津法和改进概率霍夫变换来检测车道线。对多段不同光照模式下的车道图像进行的仿真实验表明,该方法对缩微道路车道线检测的成功率达到95.5%,具有很强的鲁棒性和抗干扰能力。     

智能水滴算法研究

智能水滴算法是模拟自然界中河水与周围环境相互作用的过程而提出的一种智能计算方法。文章首先描述智能水滴算法的原理,然后综述智能水滴算法在多个研究领域的应用,最后对智能水滴算法进行总结与讨论。     

金陵电厂proFiBuS总线控制系统维护经验总结

华能金陵超超临界电厂是中国第一家在主辅控区域同时实行了PROFIBUS现场总线控制的百万机组级、全数字化电厂,现场大量使用了与传统DCS控制不同的控制网络、现场智能化设备,维护手段和方式也有别于传统的控制系统。这为数字智能化电厂的建设打下了基础,具有重要的示范意义。本文以华能金陵电厂脱硫系统的总线控制系统为例,介绍了总线方面的相关概念和知识,通过对总线功能作用的阐述,以现场总线智能设备为切入点,结合平时的维护检修工作,对PROFIBUS的优缺点进行了分析总结,并提出了今后维护工作的注意事项。     

锅炉智能吹灰优化系统的优化实施

电站燃煤锅炉受热面污染严重且吹灰不科学的现象普遍存在,极大地影响着锅炉的安全性、经济性和运行的高效性。智能吹灰系统实现了锅炉各受热面积灰程度的实时在线监测和量化处理,对吹灰过程进行智能优化指导,在受热面换热特性得到保证的情况下,最大限度降低吹灰频率,达到节能降耗、提高机组运行经济性和安全性。     

基于事件的移动智能终端侦查方法概述

侦查取证过程中,智能终端早已成为关键证据和难点。通过比对功能机和智能机的特点,针对智能终端侦查取证,提出了一套新型的基于事件分析的策略和方法,并通过工具展示基于事件分析的优势。     

Dynamic surface control-backstepping based impedance control for 5-DOF flexible joint robots

A new impedance controller based on the dynamic surface control-backstepping technique to actualize the anticipant dynamic relationship between the motion of end-effector and the external torques was presented. Comparing with the traditional backstepping method that has “explosion of terms” problem, the new proposed control system is a combination of the dynamic surface control technique and the backstepping. The dynamic surface control (DSC) technique can resolve the “explosion of terms” problem that is caused by differential coefficient calculation in the model, and the problem can bring a complexity that will cause the backstepping method hardly to be applied to the practical application, especially to the multi-joint robot. Finally, the validity of the method was proved in the laboratory environment that was set up on the 5-DOF (degree of freedom) flexible joint robot. Tracking errors of DSC-backstepping impedance control that were 2.0 and 1.5 mm are better than those of backstepping impedance control which were 3.5 and 2.5 mm in directions X, Y in free space, respectively. And the anticipant Cartesian impedance behavior and compliant behavior were achieved successfully as depicted theoretically.