公交浮动车辆到站时间实时预测模型

根据公交浮动车辆实时GPS数据, 考虑不同时段的路段平均速度、公交车站、信号灯等多因素的影响, 建立了一种新的公交车辆到站时间预测模型。通过估计到达下游最临近站点的时间和判断道路上GPS数据的有效性等方法, 改善了预测模型的精度, 并应用重庆公交车辆数据对模型进行验证。计算结果表明: 该模型能够实时预测公交浮动车辆到达下游站点的时间, 预测精度优于现有方法, 在高峰时段预测误差小于9%, 在非高峰时段预测误差约为6%, 并对各种道路交通条件具有较好的适应性。     

重型卡车驾驶室造型趋势研究

本文从整体造型风格、造型轿车化以及信息化、智能化对造型的影响等方面探讨了当代重型卡车车身造型设计的发展趋势.     

An Approach to Hide Secret Speech Information

Introduction Informationhidingasacommunicationprob-lem[1]canbeadoptedtoprotectthesecurityofme-dia(signal)andchannelofcommunication.Media securityisrelativetocopyrightprotectionofdigital media,i.e.watermarking.Channelsecurityasso-ciateswithsecurecommunication.Mostresearch todaylayparticularstressontheformer,whilelit-tleattentionispaidtothelatter.Thispaperisfo-cusedonthesecurityofcommunicationchannel,proposesanapproachofreal-timespeechsecure communicationbasedonthetechniqueinformation hiding.Th…     

Tuning of transfer functions for analysis of wave–ship interactions

Transfer functions are often used together with a wave spectrum for analysis of wave–ship interactions, where one application addresses the prediction of wave-induced motions or other types of global responses. This paper presents a simple and practical method which can be used to tune the transfer function of such responses to facilitate improved prediction capability. The input to the method consists of a measured response, i.e. time series sequences from a given sensor, the 2D wave spectrum characterising the seaway in which the measurements are taken, and an initial estimate of the transfer function for the response in study. The paper presents results obtained using data from an in-service container ship. The 2D wave spectra are taken from the ERA5 database, while the transfer function is computed by a simple closed-form expression. The paper shows that the application of the tuned transfer function leads to predictions which are significantly improved compared to using the transfer function without tuning.     

基于ANN的船舶撞击高桩码头群桩损伤位置预测

本文采用有限元软件ABAQUS建立了船舶撞击高桩码头群桩的空间有限元模型。通过计算评估了撞击力、桩体刚度、撞击位置和撞击角度下对群桩结构损伤位置的影响。基于人工神经网络(ANN)方法,对不同参数组合下的群桩结构损伤位置进行了预测,并对ANN方法的可行性进行了评估。     

浅谈信号系统侧冲防护在城市轨道交通中的应用

防侧面冲突是信号系统最基本的安全功能之一,城市轨道交通信号系统如何在兼顾安全与效率的前提下进行侧冲防护,对整个信号系统的设计尤为重要.本文重点介绍了侧冲防护的原则及其防护原理.     

Full six degrees of freedom coupled dynamic simulation of ship collision and grounding accidents

By taking advantage of the user-defined load subroutine (loadud) and the user common subroutine (usercomm) in LS-DYNA, the authors proposed a new coupled approach for simultaneously calculating structural damage and the planar 3DOF ship motions in ship collisions. The coupled procedure aimed at predicting the detailed structural damage together with reasonable global ship motions. This paper extends the method to consider the full 6DOF ship motions; thus, ship collision as well as grounding accidents can be properly handled. This method is particularly useful for design purposes because the detailed ship hull profile is not needed.A traditional ship maneuvering model is used for the in-plane surge, sway and yaw degrees of freedom with a series of nondimensional coefficients determined from experiments. It is assumed that the out-of-plane degrees of freedom are not coupled with the in-plane ship motions, and there is no coupling among roll, pitch and heave motions. The implementation is verified through free decay tests, and the obtained natural periods show good agreement with theoretical results.Several collision and grounding cases are simulated in which a supply vessel crashes into rigid plates with different orientations. The effects of the roll motion, the heave and pitch motions and the full 6DOF motions are studied. The results are compared with those from a 6DOF decoupled method. Ship motions through the proposed method compare reasonably well with SIMO results. It is found that several consecutive impacts may occur in the simulation of one collision case due to the periodic motions. This is not taken into account in the decoupled method, which makes this method unconservative.     

Strain prediction for critical positions of FPSO under different loading of stored oil using GAIFOA-BP neural network

FPSO (floating, production, storage and offloading) units are widely used in the offshore oil and gas industry. Generally, FPSOs have excellent oil storage capacity owing to their huge oil cargo holds. The volume and distribution of stored oil in the cargo holds influence the strain level of hull girder, especially at critical positions of FPSO. However, strain prediction using structural analysis tools is computationally expensive and time consuming. In this study, a prediction tool based on back-propagation (BP) neural network called GAIFOA-BP is proposed to predict the strain values of concerned positions of an FPSO model under different oil storage conditions. The GAIFOA-BP combines BP model and GAIFOA which is a combination of genetic algorithm (GA) and an improved fruit fly optimization algorithm (IFOA). Results from three benchmark tests show that the GAIFOA-BP model has a remarkable performance. Subsequently, a total of 81 sets of training data and 25 sets of testing data are obtained from experiment using fiber Bragg grating (FBG) sensors installed on the surface of an FPSO model. The numerical results show that the GAIFOA-BP is capable of predicting the strain values with higher accuracy as compared with other BP models. Finally, the reserved GAIFOA-BP model is utilized to predict the strain values under the inputs of a 10-day time series of volume and distribution of stored oil. The predicted strain results are further used to calculate the fatigue consumption of measurement points.     

基于时延特性建模的多断面短时交通流预测

针对现有交通流预测方法未充分考虑多断面车流演变规律，提出基于时延特性建模的时空相关性计算方法. 该方法采用对不同断面、不同时刻交通流的分布相似性度量，对输入的车辆到达数据序列进行切割构建时空相似度矩阵，得到相邻断面之间的时延参数. 基于时延特性建模，将多断面之间的流量信息进行融合，使用长短时记忆(LSTM)网络进行流量预测. 通过对实际路段数据的预测和结果分析，验证所提方法的有效性和实用性.