地铁架空刚性接触网平面设计软件的优化

当前地铁设计任务的不断增加对接触网辅助设计软件提出更高的要求。介绍架空刚性接触网平面设计软件的优化内容,采用先进的编程语言实现分布式软件架构,对架空刚性接触网平面设计中的底图处理、锚段智能划分、悬挂点智能布置及冲突检测和调整、拉出值自动计算、汇流排和渡线设计、工程量统计及图幅处理等算法进行优化设计。实际应用表明,本软件提高了地铁架空刚性接触网平面设计的成图质量及设计效率,可满足高质、高效的出图需求。     

基于支持向量回归机和粒子群算法的船舶操纵运动模型辨识

基于仿真的Z形试验数据,应用支持向量回归机对船舶操纵运动响应模型进行了机理建模,从核函数结构中得到了模型中的操纵性指数,并利用建立的响应模型进行了Z形试验的运动预报,同时引入粒子群算法对惩罚因子C值进行寻优,以减少惩罚因子C值选择的任意性对船舶操纵运动模型辨识精度产生的不利影响。通过将运动预报结果同仿真试验数据进行比较,验证了文中方法的有效性。     

Real-Time Transportation Mode Detection Using Smartphones and Artificial Neural Networks: Performance Comparisons Between Smartphones and Conventional Global Positioning System Sensors

Traditionally, traffic monitoring requires data from traffic cameras, loop detectors, or probe vehicles that are usually operated by dedicated employees. In efforts to reduce the capital and operational costs associated with traffic monitoring, departments of transportation have explored the feasibility of using global positioning system (GPS) data loggers on their probe vehicles that are postprocessed for analyzing the traffic patterns on desired routes. Furthermore, most cell phones are equipped with embedded assisted-GPS (AGPS) chips, and if the mode of transportation the phone is in can be anonymously identified, the phones can be treated as if they are probe vehicles that are voluntarily hovering throughout the city, at minimal additional costs. Emerging cell phones known as “smartphones” are equipped with additional sensors including an accelerometer and magnetometer. The accelerometer can directly measure the acceleration values, as opposed to having acceleration values derived from speed values in conventional GPS sensors. The magnetometer can measure mode-specific electromagnetic levels. Smartphones are subscribed with roadside Internet data plans that can provide an essential platform for real-time traffic monitoring. In this article, neural network-based artificial intelligence is used to identify the mode of transportation by detecting the patterns of distinct physical profile of each mode that consists of speed, acceleration, number of satellites in view, and electromagnetic levels. Results show that newly available values in smartphones improve the mode detection rates when compared with using conventional GPS data loggers. When smartphones are in known orientations, they can provide three-dimensional (3-D) acceleration values that can further improve mode detection accuracies.     

基于PSO算法的船用永磁电机齿槽转矩优化

高效率、高转矩密度特性使得永磁电机已被广泛应用于舰船推进领域,然而永磁电机的齿槽转矩却降低了电机的性能。永磁电机齿槽转矩受多个电机参数的影响,这些参数与电机齿槽转矩之间存在非线性关系,通过参数优化来削弱齿槽转矩成为永磁电机齿槽转矩研究的重点。提出一种基于粒子群算法的永磁电机齿槽转矩优化方法,该方法选择对齿槽转矩影响较大的极弧系数、永磁体厚度和定子槽宽度3个参数为优化变量,以齿槽转矩峰值最小为优化目标,在对永磁电机齿槽转矩解析模型进行变形和简化的基础上,使用粒子群算法对解析模型进行参数优化,得到最优参数组合,并用有限元方法进行验证。结果表明,经该优化方法优化后,电机的齿槽转矩大幅降低。     

基于改进粒子群算法的机组经济运行的博弈

在电力市场下如果能够根据实时电价求出在该电价下机组经济运行状况,可以给发电公司权衡报价风险和企业利润提供极大的帮助.如果发电公司仅依据发电成本报价,在参与竞价上网时会因缺乏灵活性而造成机组被迫频繁停机和利润空间的浪费.为此,根据企业利润最大化原则建立机组经济运行数学模型,并用改进粒子群算法对模型优化求解.通过实例分析与传统方案的预测结果进行比较,说明其效果的优劣.其给发电公司决策提供更为灵活,有效的方法.     

哈尔滨局集团公司货运智能决策支持系统研究

为加强哈尔滨局集团公司各系统间货运数据资源整合,提升营销精准度,在众多物流企业中占据竞争优势,阐述哈尔滨局集团公司铁路货运营销管理现状,针对现有信息系统缺少对市场行情、经济形势的采集和分析等问题,结合商业智能相关技术,分析当前货运营销管理决策的特点及需求,提出构建哈尔滨局集团公司货运智能决策支持系统的目标及架构,设计智能人机交互、智能搜索引擎、市场营销管理、客户行为感知、市场行情监测、自定义报表查询等功能,为哈尔滨局集团公司货运营销管理提供了重要支持。     

分动外锁闭道岔智能油润装置的设计

介绍了分动外锁闭道岔智能油润装置的结构特点、控制程序逻辑等,通过对外锁闭道岔的位置采集、道岔转换采集,以及综合气象数据和程序设置参数的计算等,得出油润时机及油润量大小,实现外锁闭道岔的精准油润,达到完全替代人工涂油作业的目的。     

CIPSO算法在城市有轨电车控制策略中的应用研究

在保证电车安全的前提下,轨道交通中的城市有轨电车控制策略优化问题实质上是多目标优化问题,主要是针对节能、正点、停靠准确和乘客舒适度优化等方面的复杂问题,以电车运动学方程为基础,针对粒子群优化算法在离散优化问题中处理不佳,容易陷入局部最优的问题,采用混沌Tent映射初始化粒子群,建立其多目标优化模型。而后采用免疫接种和免疫选择的方法提高PSO优化算法的优化能力,对模型进行求解。以广州市海珠区环岛新型有轨电车试验段数据为对象进行实例仿真,结果表明,混沌免疫微粒群优化算法较传统微粒群优化算法可获得更好的控制策略,能更有效的解决电车运行多目标优化问题。     

Floating Car Data Based Nonparametric Regression Model for Short-Term Travel Speed Prediction

A K-nearest neighbor (K-NN) based nonparametric regression model was proposed to predict travel speed for Beijing expressway. By using the historical traffic data collected from the detectors in Beijing expressways, a specically designed database was developed via the processes including data filtering, wavelet analysis and clustering. The relativity based weighted Euclidean distance was used as the distance metric to identify the K groups of nearest data series. Then, a K-NN nonparametric regression model was built to predict the average travel speeds up to 6 min into the future. Several randomly selected travel speed data series, collected from the floating car data (FCD) system, were used to validate the model. The results indicate that using the FCD, the model can predict average travel speeds with an accuracy of above 90%, and hence is feasible and effective.     

Simulation of Old Urban Residential Area Evolution Based on Complex Adaptive System

On the basis of complex adaptive system theory,this paper proposed an agent-based model of old urban residential area,in which,residents and providers are the two adaptive agents.The behaviors of residents and providers in this model are trained with back propagation and simulated with Swarm software based on environment-rules-agents interaction.This model simulates the evolution of old urban residential area and analyzes the relations between the evolution and urban management with the background of Chaozhou city.As a result,the following are obtained:(1) Simulation without government intervention indicates the trend of housing ageing,environmental deterioration,economic depression,and social filtering-down in old urban residential area.If the development of old urban residential area is under control of developers in market,whose desire is profit maximization,and factors such as social justice,historic and culture value will be ignored.(2) If the government carries out some policies and measures which will perfectly serve their original aims,simulation reveals that old urban residential area could be adapted to environment and keep sustainable development.This conclusion emphasizes that government must act as initiator and program maker for guiding residents and other providers directly in the development of old urban residential area.