检索结果-内蒙古大学图书馆

您好，读者！请登录

内蒙古大学图书馆

首页
概况
党建
资源
服务
科研支持
- 论文收录引用证明
- 科技查新
知识产权
档案馆
帮助

咨询与建议

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

您的常用邮箱：*

您的手机号码：*

问题描述：

当前已输入0个字，您还可以输入200个字

全部搜索
期刊论文
图书
学位论文
标准
纸本馆藏
外文资源发现
数据库导航
超星发现

高级检索

时间限定

出版年份：

文献类型

图书期刊文献学位论文多媒体

馆藏选择

电子馆藏纸本馆藏

核心期刊

全部期刊 SCI 收录期刊 SSCI 收录期刊 EI 收录期刊 CSCD 收录期刊 CSSCI 收录期刊

语言

中文英文

文献类型

期刊文献图书学位论文标准纸本馆藏

帮助

文字说明：

T=题名（书名、题名），A=作者（责任者），K=主题词，P=出版物名称，PU=出版社名称，O=机构（作者单位、学位授予单位、专利申请人），L=中图分类号，C=学科分类号，U=全部字段，Y=年（出版发行年、学位年度、标准发布年）

检索规则说明：

AND代表“并且”；OR代表“或者”；NOT代表“不包含”；(注意必须大写,运算符两边需空一格)

检索范例：

范例一：(K=图书馆学 OR K=情报学) AND A=范并思 AND Y=1982-2016
范例二：P=计算机应用与软件 AND (U=C++ OR U=Basic) NOT K=Visual AND Y=2011-2016

分类表

所选分类

>> <<

限定检索结果

文献类型

200 篇 会议
35 篇 期刊文献
3 册 图书

馆藏范围

238 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

166 篇 工学
- 81 篇 交通运输工程
- 68 篇 计算机科学与技术...
- 63 篇 软件工程
- 60 篇 控制科学与工程
- 41 篇 机械工程
- 20 篇 信息与通信工程
- 18 篇 电子科学与技术（可...
- 15 篇 安全科学与工程
- 13 篇 电气工程
- 11 篇 仪器科学与技术
- 10 篇 生物工程
- 8 篇 土木工程
- 8 篇 公安技术
- 6 篇 动力工程及工程热...
- 3 篇 力学（可授工学、理...
- 3 篇 材料科学与工程（可...
- 3 篇 冶金工程
- 3 篇 航空宇航科学与技...
64 篇 理学
- 47 篇 数学
- 14 篇 统计学（可授理学、...
- 12 篇 系统科学
- 10 篇 生物学
- 5 篇 物理学
- 2 篇 化学
- 2 篇 大气科学
42 篇 管理学
- 40 篇 管理科学与工程(可...
- 15 篇 工商管理
- 3 篇 图书情报与档案管...
6 篇 经济学
- 6 篇 应用经济学
3 篇 医学
- 3 篇 临床医学
1 篇 农学

主题

23 篇 rail transportat...
15 篇 safety
9 篇 rails
9 篇 delays
8 篇 trajectory
7 篇 simulation
6 篇 optimization
6 篇 feature extracti...
6 篇 mathematical mod...
5 篇 predictive contr...
5 篇 traffic control
5 篇 automation
5 篇 resistance
5 篇 real-time system...
5 篇 intelligent tran...
5 篇 decision making
5 篇 algorithm design...
5 篇 autonomous vehic...
5 篇 accuracy
4 篇 roads

机构

106 篇 state key labora...
45 篇 school of electr...
26 篇 school of traffi...
13 篇 school of automa...
12 篇 school of automa...
12 篇 beijing jiaotong...
11 篇 school of automa...
11 篇 school of electr...
10 篇 beijing jiaotong...
10 篇 state key labora...
9 篇 state key labora...
9 篇 the state key la...
7 篇 national enginee...
7 篇 beijing jiaotong...
6 篇 state key labora...
6 篇 school of comput...
6 篇 school of electr...
5 篇 state key labora...
5 篇 school of electr...
5 篇 school of electr...

作者

26 篇 hairong dong
17 篇 dong hairong
17 篇 yong qin
17 篇 wei shangguan
15 篇 limin jia
15 篇 shangguan wei
14 篇 qin yong
12 篇 baigen cai
12 篇 min zhou
12 篇 haifeng song
12 篇 tao tang
11 篇 jian wang
10 篇 tang tao
10 篇 cai baigen
9 篇 wang jian
8 篇 cai bai-gen
8 篇 ai bo
8 篇 hongjie liu
8 篇 jia limin
8 篇 shigen gao

语言

227 篇 英文
7 篇 其他
4 篇 中文

检索条件"机构=School of Automation and Intelligence and State Key Laboratory of Rail Traffic Control and Safety"

共 238 条记录，以下是121-130 订阅

全选清除本页清除全部题录导出标记到"检索档案"

详细简洁

排序：

Research on traffic Simulation Scenario Construction and Fidelity Evaluation Method under Environment of i-VICS

Research on Traffic Simulation Scenario Construction and Fid...

引用

第三十八届中国控制会议

作者： Weizhi Qiu Wei Shangguan Baigen Cai Linguo Chai School of Electronic and Information Engineering Beijing Jiaotong University State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University

Virtual traffic Simulation has always played an irreplaceable role in the study of urban transportation system, especially in intelligent vehicle infrastructure cooperative system(i-VICS), which is difficult to implement testing. A significant challenge is that the construction of large-scale simulation environment requires much time and the authenticity of the traffic simulation is doubted for various reasons. This paper presents a simulation scenario construction and fidelity evaluation method, which can build the traffic network efficiently and obtain the appraisal results easily. In this paper, the architecture and main function of traffic simulation system is analyzed firstly, which can achieve the extraction of road data and realize the construction of road network with 50 intersections covering about 18 square kilometers in 48.201 seconds. Besides the analysis on the function of system, this paper also evaluates the fidelity of simulation system. The evaluation system is mainly consisting of the construction of index system and determination of index weight. The evaluation result shows that the virtual models and traffic scenario of the simulation system has good fidelity. Thus, the traffic simulation system can meet the needs of the general simulation.

关键词： traffic Virtual Simulation Scenario Construction Fidelity Evaluation Analytic Hierarchy Process (AHP) Entropy Weight Method

来源：评论

学校读者我要写书评

暂无评论

traffic Flow Guidance and Optimization of Connected Vehicles Based on Swarm intelligence

Traffic Flow Guidance and Optimization of Connected Vehicles...

引用

第三十八届中国控制会议

作者： Qiuyan Li Wei Shangguan Baigen Cai Linguo Chai School of Electronic and Information Engineering Beijing Jiaotong University State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University

In order to solve the problem of traffic congestion and frequent accidents caused by economic, social and urban development, this paper proposes an optimization method for traffic flow guidance of connected vehicles based on vehicle-road collaborative advanced technology. In the paths between the source and destination, road resources are allocated according to the capacity and saturation constraints of the path, an adaptive multi-objective particle swarm optimization algorithm is proposed. A multi-objective optimization model of traffic flow guidance based on swarm intelligence is established. Finally, simulation results show that the proposed optimization method reduces road saturation, travel time and delay by 5.03%, 1.04% and 25.44% respectively compared with the traditional route selection method, which shows that it can improve traffic efficiency and make efficient use of road resources.

关键词： Intelligent transportation swarm intelligence multi-objective particle swarm optimization traffic flow guidance road capacity

来源：评论

学校读者我要写书评

暂无评论

Deep Reinforcement Learning Based High-level Driving Behavior Decision-making Model in Heterogeneous traffic

Deep Reinforcement Learning Based High-level Driving Behavio...

引用

第三十八届中国控制会议

作者： Zhengwei Bai Wei Shangguan Baigen Cai Linguo Chai School of Electronic and Information Engineering Beijing Jiaotong University State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University

High-level driving behavior decision-making is an open-challenging problem for connected vehicle technology, especially in heterogeneous traffic scenarios. In this paper, a deep reinforcement learning based high-level driving behavior decisionmaking approach is proposed for connected vehicle in heterogeneous traffic situations. The model is composed of three main parts: a data preprocessor that maps hybrid data into a data format called hyper-grid matrix, a two-stream deep neural network that extracts the hidden features, and a deep reinforcement learning network that learns the optimal policy. Moreover, a simulation environment, which includes different heterogeneous traffic scenarios, is built to train and test the proposed method. The results demonstrate that the model has the capability to learn the optimal high-level driving policy such as driving fast through heterogeneous traffic without unnecessary lane changes. Furthermore, two separate models are used to compare with the proposed model,and the performances are analyzed in detail.

关键词： Deep reinforcement learning high-level driving behavior decision making connected vehicle heterogeneous traffic

来源：评论

学校读者我要写书评

暂无评论

Timetable Optimization Model with Considering Regenerative Braking Power for Urban rail

Timetable Optimization Model with Considering Regenerative B...

引用

Chinese automation Congress (CAC)

作者： Juanjuan Cai Jing Xun Xiao Xiao Xiaoqing Liu Xiangyu Ji School of Electronic and Information Engineering Beijing Jiaotong University Beijing China State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing China Transit Communication and Operation Control National Engineering Laboratory for Urban Rail Beijing China Beijing Metro Operation Administration Corporation Limited Beijing China Academic of Railway Sciences (Beijing) Engineering Consult Co. Ltd Beijing China

ISBN: (数字)9781728176871

ISBN: (纸本)9781728176888

Along with China's economic growth and the urbanization is sped up. Energy conservation in urban rail transit (URT) has attracted widespread attention. Timely use of regenerative energy (URE) is an imperative way to save electricity. Regenerative braking, also known as feedback braking, is a braking technology used on electric vehicles to convert kinetic energy of train into electrical energy when the train is braking. Other trains could use these regenerative energy by accelerating in a cooperative way. In order to maximize the URE, this paper proposes a new approach that uses the train's electric power to gauge the available energy, and analyzes the operation process of a train to optimize the time when the train left the station. First, we defined 4 operating Modes of energy utilization, and codified an integer programming model. Second, we used a branch and bound algorithm to figure out the excellent result. Finally, we used the data on the operation of the Yanfang Line, Beijing Metro assessed the model. The simulation results illustrated that compared with the original timetable, the method can significantly improve the URE by 77.5%.

关键词： Optimization Acceleration rails Energy consumption Traction power supplies safety Mathematical model

来源：评论

学校读者我要写书评

暂无评论

Adaptive Tracking control with Input Saturation and Asymmetrically Time-varying Full-state Constraints for Automatic Train Operation

Adaptive Tracking Control with Input Saturation and Asymmetr...

引用

Chinese automation Congress (CAC)

作者： Yawen Sun Shigen Gao Hairong Dong Min Zhou Haifeng Song State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing China School of Electronic and Information Engineering Beijing Jiaotong University Beijing China

The state feedback tracking control problem is investigated for the train with traction and braking saturation under asymmetrically time-varying full-state constraints. To reduce the influence of input constraint, the saturation function is approximated as the sum of a smooth function and a error term. Moreover, an asymmetrically time-varying Barrier Lyapunov function is adopted to deal with the state constraints. Meanwhile, RBF and adaptive control method have been used to approximate the unknown function and estimate the unknown parameters. Hence, the proposed control method can ensure that all the signals in the close-loop system are bounded and the asymmetrically time-varying state constraints have not been violated. At last, the simulation exmaple of the train operating in fast strategy and running in the wind zone demonstrates the effectiveness of the control method.

关键词： Resistance Force Adaptation models Trajectory Wind speed safety

来源：评论

学校读者我要写书评

暂无评论

Distributed Group Consensus of A Class of Networked Heterogeneous Multi-Agent System

Distributed Group Consensus of A Class of Networked Heteroge...

引用

第三十八届中国控制会议

作者： Deheng Lian Guoguang Wen Zhaoxia Peng State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Department of Mathematics Beijing Jiaotong University School of Transportation Science and Engineering Beihang University

This paper studies the group consensus of a class of heterogeneous multi-agent systems composed of the linear firstorder, second-order and the nonlinear Euler-Lagrange agents. A class of control protocols to solve the group consensus problem is proposed, and we extend the protocol to sufficient cases including systems with leader-following network. Combining graph theory and Barbalats Lemma, we construct Lyapunov function to prove group consensus. Finally, numerical simulation results are given to illustrate the accurateness of theoretical results.

关键词： Heterogeneous Multi-agent systems Group consensus Leader Euler-Lagrange system

来源：评论

学校读者我要写书评

暂无评论

Complete Test Suites Generation of CTCS-3 Target Speed Monitor Based on Combinatorial Testing

Complete Test Suites Generation of CTCS-3 Target Speed Monit...

引用

第三十八届中国控制会议

作者： Kehang Chen Jidong Lv Zhengwei Luo Tao Tang Shigen Gao National Engineering Research Centre of Rail Transportation Operation and Control System Beijing Jiaotong University School of Electronics and Information Engineering Beijing Jiaotong University State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University

As an one-time braking mode curve, which is generated by the Target Speed Monitor（TSM） in Chinese Train control System Level 3（CTCS-3） based on the target speed, target distance, line condition, and train characteristics, performs the core safety critical functions. However, it is characterized by large parameters input domain, complex fault modes, and complicated combinations of various parameters and fault modes, which make it difficult to be effectively and efficiently tested in the train on-board equipment. In this paper, a methodology of complete test suites generated technology for the CTCS-3 TSM has been presented based on combinatorial testing（CT） strategies theory. Firstly, according to the system requirement specification（SRS）of CTCS-3, the combinatorial testing model of CTCS-3 TSM is built, which considering the selection of system parameters and its related constraints. Secondly, one of the combination strategies, in parameter order general（IPOG）, is applied to obtain the test suites under different coverage criteria. Finally, the mutation analysis has been introduced to detect the ability of the generated test suites with different faults. We also show some interesting results to compare with the test suites generated by the random testing in the same conditions.

关键词： CTCS-3 Train control System Target Speed Monitoring Combinatorial Testing

来源：评论

学校读者我要写书评

暂无评论

Defects Detection of Catenary Suspension Device Based on Image Processing and CNN

Defects Detection of Catenary Suspension Device Based on Ima...

引用

IEEE Symposium Series on Computational intelligence (SSCI)

作者： Yongguang Li Dehua Wei Xiukun Wei Kuan Wu Yong Liang Xing Shen Shengzhou Tongzhen Technology Company Beijing China School of Traffic and Transportation Beijing Jiaotong University Beijing China State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing China CRRC Changchun Rail Transit Bus Co. Ltd Changchun China

ISBN: (数字)9781728124858

ISBN: (纸本)9781728124865

Catenary suspension device (CSD) is a critical part of the pantograph-catenary system, which is a fundamental power equipment to supply electricity to urban rail transit vehicles. Whether the CSD is in a normal state is of great significance to the safe operation of operating vehicles. Therefore, it is important to detect the defects of CSD in time and automatically. In this paper, innovative and intelligent methods using image processing technologies and convolutional neural network (CNN) are proposed. Firstly, the insulators and bolts of CSD are extracted in the detected images using template matching algorithm. After that, an improved Bag of Features (BOF) model is proposed for the defect detection of CSD. Furthermore, in order to further improve the detection efficiency, AlexNet is trained for the defect detection and identification of CSD. The experimental results show that the proposed methods can detect the defects of CSD in time, with high robustness and accuracy.

关键词： Convolutional neural networks Image classification Feature extraction Image matching railway safety Fault detection

来源：评论

学校读者我要写书评

暂无评论

Multi-sensor based Train Localization and Data Fusion in Autonomous Train control System

Multi-sensor based Train Localization and Data Fusion in Aut...

引用

Chinese automation Congress (CAC)

作者： Zixing Deng Haifeng Song Hua Huang Yidong Li Hairong Dong State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing P.R. China School of Electronic and Information Engineering Beijing Jiaotong University Beijing P.R. China China Railway Hefei Train Depot Shanghai Group Co. Ltd. Hefei P.R. China School of Computer and Information Technology Beijing Jiaotong University Beijing P.R. China

ISBN: (数字)9781728176871

ISBN: (纸本)9781728176888

It is well known that one of the key technologies in train control system is the localization of train. Since multiple sensors can be installed on the train to obtain real-time data, information fusion is a promising method that can be used to combine each sensor's unique information to calculate the stable and accurate localization results. A multi-sensor based localization system for the train autonomous control is proposed in this paper, which contains the Global Positioning System, Inertial Navigation System and velocity sensor. Covariance Intersection algorithm is proposed to integrate the output results of each sensor. Besides, considering the variety of the train running environment, adaptive Kalman filter is applied to reduce the impact of environmental noise. Finally, simulation results prove the proposed method in this paper improves the positioning accuracy compared with the traditional methods.

关键词： Sensors Location awareness Covariance matrices Kalman filters Global Positioning System Sensor systems Mathematical model

来源：评论

学校读者我要写书评

暂无评论

RA-TSC: Learning Adaptive traffic Signal control Strategy via Deep Reinforcement Learning

RA-TSC: Learning Adaptive Traffic Signal Control Strategy vi...

引用

International Conference on Intelligent Transportation

作者： Yu Du Wei ShangGuan Dingchao Rong Linguo Chai School of Electronic and Information Engineering Beijing Jiaotong University Beijing China Electronic and Information Engineering the State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing China Beijing World Youth Academy

ISBN: (纸本)9781538670255

To reduce the traffic congestion, ensuring intersection control strategy efficiency is a priority in urban transportation system. Reinforcement Learning (RL)-based method provides a new possibility for solving this complex problem. In this paper, a novel region adaptive traffic signal control (RA-TSC) strategy is proposed. As an intelligent agent, the traffic signal light can learn the optimal control policy via deep reinforcement learning algorithm, namely Double Dueling Deep Q Network (3DQN). Different from the previous researches, the proposed method takes traffic characteristics into account, and two approaches are proposed to improve the performance of intersection control: trust region state (TRS) and standardized reward (SR). Besides, prioritized experience replay is adopted to guarantee algorithm stability and optimize data exploitation. Simulation results show that the proposed RA-TSC algorithm can reduce vehicle waiting length by 20% and 15.1% respectively when compared with fixed time and original 3DQN control algorithms.

关键词： Learning (artificial intelligence) Approximation algorithms Machine learning Feature extraction traffic control Roads traffic congestion

来源：评论

学校读者我要写书评

暂无评论

没有更多数据了...

全选清除本页清除全部题录导出标记到“检索档案”

共24页 << < 9 10 11 12 13 14 15 16 17 18 > >>

检索报告对象比较合并检索0

隐藏清空

合并搜索

回到顶部

执行限定条件

内容：

评分：

请选择保存的检索档案：

请选择收藏分类：

订阅名称：

通借通还

温馨提示：

图书名称：

借书校区：

取书校区：

手机号码：

邮箱地址：

一卡通帐号：

电话和邮箱必须正确填写，我们会与您联系确认。

联系人：

所在院系：

联系邮箱：

联系电话：

内蒙古自治区呼和浩特市赛罕区大学西街235号邮编: 010021

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：