后勤机动装备加装激光告警器探讨

介绍了国外车载式激光告警器的发展及装备现状,分析了现代战场上日益严峻的激光威胁环境。指出了后勤机动装备要实施安全、有效的后勤保障,就必须具备对战场激光威胁的预警能力,发出告警并指示出激光辐射源的威胁类型,使被保护目标迅速及时地采取相应措施。这对提高后勤机动装备的自我防护和生存能力,确保战时后勤物资和人员的顺畅流动,具有极其重要的意义。重点探讨了后勤机动装备加装激光告警器的必要性和可行性,并对激光告警器设计方案进行了初步论证。     

基于模糊神经网络的Horn集上的输入归结

关于定理机器证明的归结原理已应用到人工智能的很多领域，同时提出了各种改进方法，其中，输入归结是一种非常好的推理方法，它对于Horn集是完备的，模糊神经网络是模糊逻辑与神经网络的融合，文中利用模糊神经网络的知识表示及学习的特点，结合输入归结的优点，进行Horn集上的输入归结。     

基于AMFNN的非线性噪声消除器

提出基于加乘性模糊神经网络(AMFNN)的非线性噪声消除器，讨论了AMFNN模型和学习算法及其通用逼近性．该消除器利用AMFNN逼近噪声，然后从测量信号中消去噪声即得到有用信号．该噪声消除器具有神经网络分布式并行信息处理能力、较好的容错性和鲁棒性以及除噪性能．     

铁路枢纽作业轮廓计划优化模型及算法

本文给出铁路枢纽日常运输组织工作轮廓计划多商品时空网络流模型及算法，对次日枢纽内大小车流、机车应用配合我纽内各站装、卸、排空计划作出合理安排。揭示枢纽内各站次日工作的重点与关键。为进一步编制日班计划及阶段计划提供指导及辅助决策基础。     

神经网络在车辆半主动控制中的应用

针对车辆半主动悬挂模型的非线性特性，研究了采用神经网络的自适应控制在车辆悬挂半主动控制中的应用，设计了采用前馈神经网络的辩识器和控制器，对控制器网络采用的学习规则进行了分析。仿真计算表明，采用神经网络自适应控制方法能有效改善车辆的平稳性，采用的神经网络辩识器和控制器的改进BP算法是有效的。     

IP ADDRESS AUTOCONFIGURATION FOR WIRELESS AD HOC NETWORKS

IntroductionWireless ad hoc networks are gaining increas-ing popularity in recent years because of their easeof deployment. No wired base station or infras-tructure is supported,and each hostcommunicatesone anothervia packetradios. In ad hoc networks,routing protocols are challenged with establishingand maintaining multihop routes in the face of mo-bility,bandwidth limitation and power con-straints. In ad hoc networks,each node( host)acts as a router since routes are mostly multihop.Nodes in …     

Development of a driving cycle for Colombo,Sri Lanka: an economical approach for developing countries

Financial constraints and lack of availability of traffic‐related information significantly hinder the development of driving cycles in developing countries. This paper proposes an economical, practical, accurate methodology for the development of driving cycles, including the development of a driving cycle for Colombo, Sri Lanka. The proposed methodology captures regional traffic and road conditions and selects a model that represents the collected data sample with minimum available traffic‐related information. Existing methods were modified for route selection by dividing routes into links using nodes or physical junctions to minimize the number of trips required for data collection. Speed–time data for respective links were used to reconstruct speed–time profiles of identified origin–destination pairs. The on‐board method was used for data collection, and the Markov chain theory was used to develop a transition probability matrix of state changes. An additional matrix was introduced to the existing method to improve model representativeness to the collected data sample. Copyright © 2016 John Wiley & Sons, Ltd.     

Practicability study on the suitability of artificial,neural networks for the approximation of unknown steering torques

For steer-by-wire systems, the steering feedback must be generated artificially due to the system characteristics. Classical control concepts require operating-point driven optimisations as well as increased calibration efforts in order to adequately simulate the steering torque in all driving states. Artificial neural networks (ANNs) are an innovative control concept; they are capable of learning arbitrary non-linear correlations without complex knowledge of physical dependencies. The present study investigates the suitability of neural networks for approximating unknown steering torques. To ensure robust processing of arbitrary data, network training with a sufficient volume of training data is required, that represents the relation between the input and target values in a wide range. The data were recorded in the course of various test drives. In this research, a variety of network topologies were trained, analysed and evaluated. Though the fundamental suitability of ANNs for the present control task was demonstrated.     

车载网络中基于群签名的可保护隐私的车辆认证

安全和隐私是配置车载网络时所需要的2个重要条件,具有保护隐私功能的认证是实现这2个条件的关键技术.不同于已有的认证方案,文中用群签名来实现车载网络中能保护隐私的车辆认证.为了满足认证的快速性要求,基于目前安全性最强、效率较高和签名较短的ZL 06局部验证者撤销短群签名方案,提出了2个具有隐私保护功能的车载网络中的车辆认证方案.群签名所具有的良好性质保证了所提出的认证方案具有实用性和隐私保护功能.     

一种基于神经网络的馈线自适应继电保护技术

针对常规保护的自适应能力及检测某些复杂故障方面存在一定局限性,利用前馈神经网络,导出了常规保护与神经网络参数间的显式关系,证明了神经网络继电保护可实现常规馈线保护的功能。