机构

• 自动化研究所 [4]
• 地理科学与资源研究所 [3]
• 计算技术研究所 [2]
• 长春光学精密机械与物... [2]
• 数学与系统科学研究院 [1]
• 沈阳自动化研究所 [1]
• 更多

采集方式

• OAI收割 [13]

内容类型

• 期刊论文 [8]
• 会议论文 [3]
• 学位论文 [2]

发表日期

• 2022 [1]
• 2017 [3]
• 2014 [1]
• 2013 [1]
• 2011 [4]
• 2009 [1]
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学科主题

筛选

浏览/检索结果: 共13条，第1-10条 帮助 条数/页： 5101520253035404550556065707580859095100 排序方式： 请选择题名升序题名降序发表日期升序发表日期降序提交时间升序提交时间降序作者升序作者降序 Ego-efficient lane changes of connected and automated vehicles with impacts on traffic flow 期刊论文  OAI收割 TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES, 2022, 卷号: 138, 页码: 25 作者:  Wang, Yibing;  Wang, Long;  Guo, Jingqiu;  Papamichail, Ioannis;  Papageorgiou, Markos   |  收藏  |  浏览/下载：39/0  |  提交时间：2022/07/25 Ego-efficient Lane Changes  Traffic Flow Impacts  Microscopic Simulation  Reinforcement Learning   A self-learning system for local ramp metering with queue management 期刊论文  OAI收割 TRANSPORTATION PLANNING AND TECHNOLOGY, 2017, 卷号: 40, 期号: 2, 页码: 182-198 作者:  Lu, Chao;  Huang, Jie   |  收藏  |  浏览/下载：36/0  |  提交时间：2019/09/25 Intelligent transport systems  traffic flow model  ramp metering  reinforcement learning  simulation   A self-learning system for local ramp metering with queue management 期刊论文  OAI收割 TRANSPORTATION PLANNING AND TECHNOLOGY, 2017, 卷号: 40, 期号: 2, 页码: 182-198 作者:  Lu, Chao;  Huang, Jie   |  收藏  |  浏览/下载：23/0  |  提交时间：2019/09/25 Intelligent transport systems  traffic flow model  ramp metering  reinforcement learning  simulation   A self-learning system for local ramp metering with queue management 期刊论文  OAI收割 TRANSPORTATION PLANNING AND TECHNOLOGY, 2017, 卷号: 40, 期号: 2, 页码: 182-198 作者:  Lu, Chao;  Huang, Jie   |  收藏  |  浏览/下载：25/0  |  提交时间：2019/09/25 Intelligent transport systems  traffic flow model  ramp metering  reinforcement learning  simulation   Crowd Simulation and Its Applications: Recent Advances 期刊论文  OAI收割 JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY, 2014, 卷号: 29, 期号: 5, 页码: 799 作者:  Xu MingLiang;  Jiang Hao;  Jin XiaoGang;  Deng Zhigang   |  收藏  |  浏览/下载：5/0  |  提交时间：2023/12/04 SOCIAL FORCE MODEL  PEDESTRIAN BEHAVIOR  TRAFFIC SIMULATION  NAVIGATION  ANIMATION  ENVIRONMENTS  EVACUATION  FLOW  FIELDS  crowd simulation  emergency evacuation  pedestrian crowd  crowd formation  traffic simulation  swarm simulation   A Study of Destination Selection Model Based on Link Flows 期刊论文  OAI收割 IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2013, 卷号: 14, 期号: 1, 页码: 428-437 作者:  Ye, Peijun;  Wen, Ding 收藏  |  浏览/下载：20/0  |  提交时间：2015/08/12 Destination selection  link flow  traffic simulation   Enhancing network transmission capacity by efficiently allocating node capability 期刊论文  OAI收割 PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2011, 卷号: 390, 期号: 2, 页码: 387-391 作者:  Zhang, Guo-Qing;  Zhou, Shi;  Wang, Di;  Yan, Gang;  Zhang, Guo-Qiang   |  收藏  |  浏览/下载：19/0  |  提交时间：2019/12/16 Network  Transmission capacity  Traffic flow simulation  Network modelling  Power law  Network topology  Betweenness   Energy-consumption-related robust optimization scheduling strategy for elevator group control system (EI CONFERENCE) 会议论文  OAI收割 2011 IEEE 5th International Conference on Cybernetics and Intelligent Systems, CIS 2011, September 17, 2011 - September 19, 2011, Qingdao, China 作者:  Wang F.;  Wang F. 收藏  |  浏览/下载：35/0  |  提交时间：2013/03/25 Group elevator scheduling (GES) problem is an optimization problem. In this work  a robust optimization scheduling method is proposed to solve elevator group control system problem with passenger traffic flow uncertainty. An uncertain optimization model of elevator group scheduling is set up based on considering both energy consumption and waiting time. When considering the uncertainty of passenger traffic flow  the model is an uncertain optimization problem. It is tuned into its robust counterpart (RC) based on robust optimization theory. The simulation experiment presents the proposed scheduling method's scheduling performance. 2011 IEEE.   Neural network based online traffic signal controller design with reinforcement training (EI CONFERENCE) 会议论文  OAI收割 14th IEEE International Intelligent Transportation Systems Conference, ITSC 2011, October 5, 2011 - October 7, 2011, Washington, DC, United states Dai Y.; Hu J.; Zhao D.; Zhu F. 收藏  |  浏览/下载：31/0  |  提交时间：2013/03/25 Traffic congestion leads to problems like delays  decreasing flow rate  and higher fuel consumption. Consequently  keeping traffic moving as efficiently as possible is not only important to economy but also important to environment. Traffic system is a large complex nonlinear stochastic system. Traditional mathematical methods have some limitations when they are applied in traffic control. Thus  computational intelligence (CI) technologies gain more and more attentions. Neural Networks (NNs) is a well developed CI technology with lots of promising applications in traffic signal control (TSC). In this paper  a neural network (NN) based signal controller is designed to control the traffic lights in an urban traffic road network. Scenarios of simulation are conducted under a microscopic traffic simulation software. Several criterions are collected. Results demonstrate that through online reinforcement training the controllers obtain better control effects than the widely used pre-time and actuated methods under various traffic conditions. 2011 IEEE.   Pricing Scheme based Nash Q-learning Flow Control for Multi-user Network 会议论文  OAI收割 International Conference on Materials, Mechatronics and Automation (ICMMA 2011), Melbourne, AUSTRALIA, JAN 15-16, 2011 作者:  Li X(李鑫);  Yu HB(于海斌) 收藏  |  浏览/下载：25/0  |  提交时间：2012/05/29 Computer simulation  Controllers  Costs  Flow control  HIgh speed networks  Mechatronics  Quality of service  Time varying networks  Traffic congestion