A Bintree Energy Approach for Colour Image Segmentation Using Adaptive Channel Selection

A new hierarchical approach called bintree energy segmentation was presented for color image seg-mentation. The image features are extracted by adaptive clustering on multi-channel data at each level and used as the criteria to dynamically select the best chromatic channel, where the segmentation is carried out. In this approach, an extended direct energy computation method based on the Chan-Vese model was proposed to segment the selected channel, and the segmentation outputs are then fused with other channels into new images,from which a new channel with better features is selected for the second round segmentation. This procedure is repeated until the preset condition is met. Finally, a binary segmentation tree is formed, in which each leaf represents a class of objects with a distinctive color. To facilitate the data organization, image background is employed in segmentation and channels fusion. The bintree energy segmentation exploits color information involved in all channels data and tries to optimize the global segmentation result by choosing the "best" chan-nel for segmentation at each level. The experiments show that the method is effective in speed, accuracy and flexibility.     

基于MapInfo的城市公交出行最优路线算法研究

根据城市交通网络的特点,利用动态分段技术建立的基于MapInfo的动态分段数据结构,充分考虑了乘客出行心理,同时设计出了公交出行最优路径算法,已经济南市公交信息查询系统的实践证明,提高了乘客出行的便利性和高效性。     

基于图像处理的路面裂缝识别研究

传统的人工视觉检测裂缝方法具有耗力、耗时、不精确、影响交通、危险、花费高等缺点。这里介绍一种基于图像处理的路面裂缝类病害自动识别方法。首先使用一种掩膜平滑法,对有大量噪音的路面图像进行增强,再采用最大类间、类内距离准则对图像进行阈值分割,提取图像上的裂缝特征,实验结果表明了该方法的有效性。     

一种新型故障限流器的设计和仿真

采用短路电流限制器(FCL)快速限制短路电流是提高系统稳定性和断路器开断能力的有效方法之一.文中提出一种新型的具有串联补偿功能的故障电流限流器,它由补偿电容和旁路电感并联后与限流电感串联而成;和旁路电感相串联的可关断晶闸管(GTO)控制正常时的补偿度和故障时的限流程度.用MATLAB对传输线路短路的仿真分析证明此装置效果良好,是电力系统中有用的保护设备.     

短期货运预测模型研究

短期货运量的预测对于交通运输系统的运作与管理具有重要意义．本文将回归分析与时间序列分析相结合,提出一个带有回归项和时间序列误差项的回归-时序混合模型,用以进行短期货运量的预测．在对模型进行识别、初估计的基础上,采用极大似然方法进行参数估计,经反复拟合,并对模型进行相应检验,最后得到符合要求的拟合模型。应用此回归-时序混合模型进行月度货运量的拟合预测,并与多元线性回归模型和季节ARIMA模型的拟合预测结果相比较,表明回归-时序混合模型可以提高短期货运量的预测精度。     

Measuring Truck Travel Time Reliability Using Truck Probe GPS Data

Truck probe data collected by global positioning system (GPS) devices has gained increased attention as a source of truck mobility data, including measuring truck travel time reliability. Most reliability studies that apply GPS data are based on travel time observations retrieved from GPS data. The major challenges to using GPS data are small, nonrandom observation sets and low reading frequency. In contrast, using GPS spot speed (instantaneous speed recorded by GPS devices) directly can address these concerns. However, a recently introduced GPS spot-speed-based reliability metric that uses speed distribution does not provide a numerical value that would allow for a quantitative evaluation. In light of this, the research described in this article improves the current GPS spot speed distribution-based reliability approach by calculating the speed distribution coefficient of variation. An empirical investigation of truck travel time reliability on Interstate 5 in Seattle, WA, is performed. In addition, correlations are provided between the improved approach and a number of commonly used reliability measures. The reliability measures are not highly correlated, demonstrating that different measures provide different conclusions for the same underlying data and traffic conditions. The advantages and disadvantages of each measure are discussed and recommendations of the appropriate measures for different applications are presented.     

船舶动力定位能力分析程序开发研究

本文根据船舶动力定位系统的工作原理,基于MATLAB语言将环境载荷计算、推力计算、推力分配、图形绘制等功能进行集成,完成动力定位能力频域分析模块开发;然后结合Kalman滤波算法采用LQR方法进行反馈控制,完成时域分析模块开发。以某型海洋调查船为算例,首先,利用该程序绘制了动力定位能力曲线,并且与Kongsberg Maritime分析报告对比,结果吻合良好,为推进器的选型与布置提供依据;然后,进行时域模拟给出海洋调查船的位置、姿态的时历曲线和各个推进器的推力响应情况,为实际工程提供指导。     

基于CFD的一种无压载水船阻力数值模拟

为解决船舶压载水问题,在无压载水船设计理念贯通流系统的基础上,利用连通管路对其进行改造,提出一种船舶无压载水化新思路。同时,以系列60船型改造后的新船型作为研究对象,基于CFD方法,选用混合网格和RNG 湍流模型对其进行阻力数值模拟,利用黏性流对叠模求解。为验证网格划分和数值方法的合理性,首先,对系列60船型进行数值模拟,计算结果与传统实验数据基本吻合。然后,对新船型进行阻力数值模拟,并将其与系列60船型的阻力数据进行比较分析。结果表明,新船型降低了船舶阻力,优化了水动力性能。     

基于自动文本分析的船舶避碰案例学习模型

构建基于自然语言处理的案例学习模型,以文本形式描述的船舶避碰案例,通过自动分词、消岐和语义分析等步骤,从中提取和生成以框架形式描述的避碰案例,并将其存储在计算机中。仿真试验表明,该模型可以实现避碰案例从文本文件到可用案例的有效转换,为案例学习提供新的方法。