基于贝叶斯网络的辐射源威胁等级评估算法

贝叶斯网络是近年来人工智能领域最重要的研究成果之一，在具有不确定性的推理和决策问题中得到了广泛的应用。以贝叶斯网络及其推理机制为基础，主要研究了贝叶斯网络在辐射源威胁等级评估方面的应用。选取了部分影响因素，建立了基于贝叶斯网络的辐射源威胁等级评估模型。最后通过一个计算机仿真实例验证了算法具有连续性和累积性，能够对辐射源威胁等级做出较准确评估。     

Simulation of the mean zero-up-crossing wave period using artificial neural networks trained with a simulated annealing algorithm

The aim of this work was to develop a predictive model to forecast the mean zero-up-crossing wave periods (T _z ) for 3-hourly sea states at a location in the Pacific using artificial neural networks (ANNs). Seven multilayer ANNs were trained with a simulated annealing algorithm. The output of each trained ANN was used to estimate each of the seven parameters of a new distribution called the hepta-parameter spline proposed for the conditional distribution of T _z , given some mean zero-up-crossing wave periods and significant wave heights. After estimating the parameters of the distribution, the model was used to simulate and predict future values of T _z . Forecasting a sea state and developing the joint distribution of sea state characteristics with the help of the simulated characteristics are also discussed in this article.     

Economic Viability of Mega-size Containership in Different Service Networks

The mega-size containership viability was analyzed by considering different service networks for different ship sizes: hub-and-spoke and multi-port-calling (MPC) networks for mega-size containerships and conventional ships. A model was proposed, which quantifies the economies of scale in operating large con- tainerships and constructs models for ship routing under different service networks. A sensitivity analysis was conducted to test the effect of feeder costs and the results analyzed to determine optimal containership size with respect to different operational scenarios. Throughout model applications for Asia-Europe and Asia-North America trades, the mega-size containership is competitive in all scenarios for Asia-Europe, while it is viable for Asia-North America only when the feeder costs are low.     

用GPS技术建立城市测量控制网的试验研究

本文以广德ＧＰＳ网为试验对象，对于中等精度ＧＰＳ测量的建网方法、基线向量的解算、卫星网与地面网的配置等问题进行了研究，取得了对生产实践有益的结论。     

电铁监控系统通信网络及其智能通信设备的研究

本文通过对电气化铁道监控系统通信网络结构的分析，提出了适用的网络结构及其备用方式，设计了相应的智能通信设备，整个通信网络具有较高的性能价格比，同时使系统的可靠性和实时性得到很大提高。     

A NARX damper model for virtual tuning of automotive suspension systems with high-frequency loading

A computationally efficient NARX-type neural network model is developed to characterise highly nonlinear frequency-dependent thermally sensitive hydraulic dampers for use in the virtual tuning of passive suspension systems with high-frequency loading. Three input variables are chosen to account for high-frequency kinematics and temperature variations arising from continuous vehicle operation over non-smooth surfaces such as stone-covered streets, rough or off-road conditions. Two additional input variables are chosen to represent tuneable valve parameters. To assist in the development of the NARX model, a highly accurate but computationally excessive physical damper model [originally proposed by S. Duym and K. Reybrouck, Physical characterization of non-linear shock absorber dynamics, Eur. J. Mech. Eng. M 43(4) (1998), pp. 181–188] is extended to allow for high-frequency input kinematics. Experimental verification of this extended version uses measured damper data obtained from an industrial damper test machine under near-isothermal conditions for fixed valve settings, with input kinematics corresponding to harmonic and random road profiles. The extended model is then used only for simulating data for training and testing the NARX model with specified temperature profiles and different valve parameters, both in isolation and within quarter-car vehicle simulations. A heat generation and dissipation model is also developed and experimentally verified for use within the simulations. Virtual tuning using the quarter-car simulation model then exploits the NARX damper to achieve a compromise between ride and handling under transient thermal conditions with harmonic and random road profiles. For quarter-car simulations, the paper shows that a single tuneable NARX damper makes virtual tuning computationally very attractive.     

山区高速公路桥隧段行车安全评价模型研究

桥隧连接段属于道路环境突变段。研究表明在道路环境突变段所产生的交通事故多为恶性事故,为了改善桥隧段的行车安全,利用模糊理论的相关方法来评价桥隧段行车的安全性,并在计算隶属函数隶属度的时引入人工神经网络的相关理论,避免了确定隶属函数时的主观性和模糊性;在方法类型的角度,使用模糊理论来评价桥隧段行车的安全性,在评价时使用了多个层次、多个因素的分析方法,在解决道路行车安全评价时具有一定的优越性,使得评价更趋于精确,客观。     

多跳水下传感器网络中的功率分配算法

水下无线传感器网络的研究越来越受到学术界的重视,其典型特点是能量和带宽有限.多数水下无线传感器网络的应用都可以归结为参数估计问题.本文针对多跳水下无线传感器网络,对递进式的分布式参数估计算法进行了性能分析.在此基础上,利用交替最小化方法得到功率分配方案,目标是在给定的均方误差性能要求下,使得网络消耗的总功率最小.     

舰船电力电子设备在线阻抗建模方法

从二端口网络分析出发,设计一种基于差分方式的在线阻抗测试方法。运用人工神经网络的优化方法,提出一种阻抗等效电路参数的提取算法,由此建立在线阻抗等效电路模型。应用该方法实现了电力电子设备阻抗的在线工程测量,实测与仿真结果表明基于该建模方法所获得的阻抗等效电路能准确反映设备在线运行的阻抗特征。     

基于事件触发的无线传感器网络动态分簇

针对由目标事件激发的无线传感器网络动态分簇问题,提出了一种动态分簇协议。着重研究了簇头竞选,成员招募和簇重组等关键环节,在簇头竞选机制中,提出了一种综合考虑了节点接收信号强度,剩余能量以及与汇聚节点的距离等因素的竞选方案。在簇成员招募阶段,提出了一种基于任务需求的自适应簇范围划分方法,约束了簇的规模,降低了簇内通信的能耗。仿真结果表明：该协议能够有效地节省节点能量,延长网络寿命,尤其适用于汇聚节点距离网络较远的情况。