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A Clustering-Based Routing Protocol Using Path Pattern Discovery Method to Minimize Delay in VANET

Wireless Communications and Mobile computing 2023年第1期2023卷

作者： Xie, Xiaoyun Navaei, Yahya Dorostkar Einy, Sajad School of Electronic Information Engineering Gannan University of Science and Technology Jiangxi Ganzhou341000 China Ganzhou Key Laboratory of Cloud Computing and Big Data Jiangxi Ganzhou341000 China Computer and Information Technology Engineering Qazvin Branch Islamic Azad University Qazvin Iran Istanbul Aydin University Department of Application and Research Center for Advanced Studies Istanbul Turkey

In vehicular ad hoc networks (VANETs), vehicle-to-vehicle (V2V) communications can link vehicles to each other, and vehicle-to-infrastructure (V2I) messaging and communications can link roadside infrastructure such as routers. The vehicles in these networks act as relays that transmit critical messages in the network. Due to the high-speed movement of vehicles on the road, real-time messaging and minimizing the delay in sending messages is one of the most important objectives of VANET developers. On the other hand, the high mobility of vehicles causes communication interruptions and decreases the data delivery rate in VANET. To overcome this issue, predicting the path of vehicles can play an important role in sending data from the source to the destination. When an accident occurs on the road, the messages that are sensed by the imbedded sensors in the vehicles need to be sent, and if they are sent by the vehicles that change their route, these messages will not be sent to the destination and the performance of the network will be disturbed. Previous methods in the literature for data transmission in intervehicular networks have focused more on reliability and trust, and little attention has been paid to the prediction of vehicle movement paths in these types of networks. Therefore, for fast and reliable data transmission in VANET, accurate prediction of vehicle movement and creation of movement patterns can be effective in message transmission delay and data delivery rate. In this paper, we present an approach using a combination of cluster-based routing protocols and pattern discovery methods to minimize latency in VANETs. The outline of the proposed method has four modules: primary data collection and analysis, primary data preparation and analysis, pattern extraction and vehicle route discovery, and vehicle clustering and data/information transmission routing. The simulation results show that the proposed method with a delivery rate of 88.56% has significantly i

关键词： Vehicular ad hoc networks

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Text Semantic Analysis and Intelligent Interaction in Parallel Dispatching Systems for Technical Station

Text Semantic Analysis and Intelligent Interaction in Parall...

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Digital Twins and Parallel Intelligence (DTPI), IEEE International Conference on

作者： Yuantao Jiao Jian Wang Runmei Li Gang Xiong Shichao Chen School of Automation and Intelligence Beijing Jiaotong University Beijing China Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing China Guangdong Engineering Research Center of 3D Printing and Intelligent Manufacturing Cloud Computing Center Chinese Academy of Sciences Dongguan China State Key Laboratory for Multimodal Artificial Intelligence Systems Chinese Academy of Sciences Beijing China

ISBN: (数字)9798350349252

ISBN: (纸本)9798350349269

Technical station dispatching system plays an important role in cargo operation, but due to the large number of dispatching systems and complex operation, dispatchers rely on manual experience to complete the task, and many scenarios cannot be applied in the real system. Therefore, this paper utilizes the data-driven form to establish a parallel dispatching system for technical stations, semantically analyzes text data rich in dispatcher experience, completes the Computational Experiments on the textual semantic data in the artificial dispatching system, and synchronizes the Parallel Execution of data interaction with the real dispatching system.

关键词： Training Analytical models Semantics Dispatching Digital twins Synchronization Feeds

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An Actor-Critic Framework Deep Reinforcement Learning Approach to High-speed Train Timetable Rescheduling Problem

An Actor-Critic Framework Deep Reinforcement Learning Approa...

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Digital Twins and Parallel Intelligence (DTPI), IEEE International Conference on

作者： Zhilong Tian Runmei Li Gang Xiong Fenghua Zhu School of Automation and Intelligence Beijing Jiaotong University Beijing China Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing China Guangdong Engineering Research Center of 3D Printing and Intelligent Manufacturing Cloud Computing Center Chinese Academy of Sciences Dongguan China State Key Laboratory for Multimodal Artificial Intelligence Systems Chinese Academy of Sciences Beijing China

ISBN: (数字)9798350349252

ISBN: (纸本)9798350349269

High-speed trains are inevitably affected by emergencies in their daily operation, which may cause the trains to fail to run according to the original planned timetable. Therefore, how to adjust the timetable of subsequent trains in emergencies is crucial for railway operations. This paper introduces a deep reinforcement learning algorithm based on an actor-critic network, which minimizes the total delay time by defining the departure order as an action. Numerical experiments are performed on the timetable of Beijing-Shanghai high-speed railway line.

关键词： Optimization models Deep reinforcement learning Rail transportation Dispatching Digital twins Delays Optimization

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EG-KGR: A Knowledge Graph Reasoning Model Based on Enhanced Graph Sample and Aggregate Inductive Learning Algorithm

EG-KGR: A Knowledge Graph Reasoning Model Based on Enhanced ...

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International Conference on Tools for Artificial Intelligence (ICTAI)

作者： Yuejia Wu Jian-Tao Zhou Inner Mongolia Key Laboratory of Discipline Inspection and Supervision Big Data Inner Mongolia Engineering Laboratory for Big Data Analysis Technology Ministry of Education Inner Mongolia Engineering Laboratory for Cloud Computing and Service Software Inner Mongolia Key Laboratory of Social Computing and Data Processing College of Computer Science Inner Mongolia University National & Local Joint Engineering Research Center of Intelligent Information Processing Technology for Mongolian Engineering Research Center of Ecological Big Data Hohhot China

Knowledge Graph is an important research field that involves the storage and management of knowledge, but the incompleteness and sparsity of Knowledge Graphs hinder their application in many fields. Knowledge Graph Reasoning aims to alleviate this problem by completing missing paths or identifying wrong paths between entities. Graph Convolution Network (GCN) based methods are one of the state-of-the-art approaches to this work. However, it is difficult to directly generalize to unknown nodes and utilizes valid information from the local neighborhood which results in poor flexibility and extensibility and will loss of important information. This paper presents EG-KGR, a plug-and-play knowledge reasoning model based on enhanced graph sampling and aggregate inductive learning algorithm to relieve the above problems and enhance existing GCN-based methods. Specifically, EG-KGR supports incremental characteristics, uses inductive learning to replace transductive learning, and designs random sampling and local information sampling optimization methods to improve the model's generalization ability, prediction accuracy, and running speed. Extensive experimental results show that our EG-KGR can achieve optimal results.

关键词： Training Knowledge engineering Convolution Aggregates Optimization methods Knowledge graphs Learning (artificial intelligence)

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A Geometry Aware Diffusion Model for 3D Point cloud Generation

A Geometry Aware Diffusion Model for 3D Point Cloud Generati...

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IEEE International Conference on Automation Science and Engineering (CASE)

作者： Ao Zhang Zhen Shen Qihang Fang Jian Yang Gang Xiong Xisong Dong State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences Beijing China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing China Guangdong Engineering Research Center of 3D Printing and Intelligent Manufacturing Cloud Computing Center Chinese Academy of Sciences Dongguan China

ISBN: (数字)9798350358513

ISBN: (纸本)9798350358520

Point clouds have increasingly become the preferred representation for various visual and graphical applications. Denoising diffusion probability models (DDPMs) have demonstrated remarkable applications in areas such as 3D point cloud generation. Furthermore, the ability to generate or reconstruct high-resolution, high-fidelity point clouds stands as a pivotal requirement within this domain. To this end, we propose a geometry aware diffusion model for 3D shape generation. Considering that the global latent shape space overlooks the inherent topology and fine-grained information within the 3D shape itself, we introduce a geometry latent space that operates in a cascaded relationship with the global shape latent space. This latent space combines the global shape latent with the geometry latent space. To generate high-quality point clouds, we conduct training on the geometry latent space, which yields superior results compared to training solely on the global shape latent space. Specifically, we represent the point cloud as a set of unordered point representations with positional embedding. We further employ a geometry aware attention block to model global geometric relationships and retaining local detail features, capturing the inductive bias of the 3D geometric structure of the point cloud. We conduct experiments across various ShapeNet benchmarks, and our approach has demonstrated substantial advancements in the generation of point clouds when compared to the baseline.

关键词： Point cloud compression Geometry Training Solid modeling Visualization Three-dimensional displays Shape Noise reduction Diffusion models Topology

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Architecture and Key Technologies of Parallel Dispatching System for Railway Technical Operation Stations

Architecture and Key Technologies of Parallel Dispatching Sy...

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2023 International Annual Conference on Complex Systems and Intelligent Science, CSIS-IAC 2023

作者： Xiong, Gang Yang, Donghu Xu, Wei Li, Runmei Chen, Shichao Song, Bing Dong, Xisong Zhu, Fenghua Institute of Automation Chinese Academy of Sciences State Key Laboratory of Multimodal Artificial Intelligence Systems Beijing100190 China Institute of Automation Chinese Academy of Sciences Beijing Engineering Research Center of Intelligent Systems and Technology Beijing100190 China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing100049 China Signal and Communication Research Institute China Academy of Railway Science Corporation Limited Beijing100081 China The School of Electronic and Information Engineering Beijing Jiaotong University Beijing100081 China Beijing Huairou Academy of Parallel Sensing Beijing101400 China Chinese Academy of Sciences Guangdong Engineering Research Center of 3D Printing and Intelligent Manufacturing Cloud Computing Center Dongguan523808 China

ISBN: (纸本)9798350309003

A railroad technical operation station is an extensive and complex operation system and a variety of random disturbing factors further increase the complexity of its command and dispatching. To enhance the railroad technical operation stations' intelligence, and integration level, and enhance its dispatching management ability of complex operation plans, based on the ACP approach, this paper designs the parallel dispatching system (PDS) architecture, and describes its key technologies including the artificial dispatching system (ADS), computing experiments, parallel execution, etc. On the basis of the artificial dispatching system, computational experiments can optimize various types of technical operations and the overall operational process, to achieve parallel execution between the actual dispatching system and ADS. PDS can provide more efficient and intelligent command and dispatching solutions for railroad technical work stations, and promote the development of the railroad transportation industry in the direction of higher quality and efficiency. © 2023 IEEE.

关键词： Railroads

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Fast calibration of agent-based model using mean-field approach 1

Fast calibration of agent-based model using mean-field appro...

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1st IEEE International Conference on Digital Twins and Parallel Intelligence, DTPI 2021

作者： Lu, Wanze Xiong, Gang Liu, Xudong Liu, Sheng Ye, Peijun Zhang, Liguo Beijing University of Technology Faculty of Information and Technology Beijing China The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China The Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing China The Guangdong Engineering Research Center of 3D Printing and Intelligent Manufacturing The Cloud Computing Center Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781665433372

Calibration of simulation system is an important step to establish a reliable simulation system. In this paper, based on the existing mean field calibration theory, a new fast calibration method for complex urban traffic system based on mean field method is discussed by establishing the relationship between the macroscopic observation quantity and the proxy microscopic parameters. This method makes use of the machine learning method, and reduces the dimension of the state vector in the discrete time period, so that the dimension of the macroscopic state transition matrix is lower, and then reduces the computational complexity of the system calibration. Finally, the calibration results of the simulation system were verified by SUMO traffic simulation software. © 2021 IEEE.

关键词： Calibration

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Application of 3D vision intelligent calibration and imaging technology for industrial robots

Application of 3D vision intelligent calibration and imaging...

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2021 Guangdong-Hong Kong-Macao Greater Bay Area Artificial Intelligence and Big Data Forum, AIBDF 2021

作者： Yang, Rui Mo, Qinglong Li, Yuhong Liu, Yizhi Hu, Ruihan Guangdong Institute of Intelligent Manufacturing Guangdong Key Laboratory of Modern Control Technology Guangzhou510070 China Cloud Computing Center Chinese Academy of Sciences Dongguan523808 China Guangdong Key Laboratory of Modern Control Technology Guangdong Institute of Intelligent Manufacturing Guangzhou China Engineering Research Center of Intelligence Perception and Autonomous Control Ministry of Education Beijing China Xinjiang Production and Construction Corps Key Laboratory of Modern Agricultural Machinery Shihezi University Shihezi China

During modern flexible lean manufacturing, flexible operation of irregular and complex workpieces with different specifications and arbitrary placement is an essential ability of industrial robots, while it cannot be met by traditional clamping methods. Vision technology brings flexibility and convenience to industrial robots, but the common two-dimensional technology only involves three degrees of freedom (plane displacement and rotation), which hinders the positioning of arbitrarily placing workpieces (often six degrees of freedom) and disorderly sorting. In addition, for typical visual tasks in industrial environments like defect detection, accurate distinguishing of such defects as pits and scratches is challenging under two-dimensional plane imaging. The introduction of three-dimensional information provides an effective solution to this problem. Thus, in the face of increasingly complex, flexible, intelligent and personalized manufacturing needs, the acquisition and processing of 3D visual information are of much importance. © 2021 Institute of Physics Publishing. All rights reserved.

关键词： Vision

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An interpretability analysis of travel decision learning in cyber-physical-social-systems 1

An interpretability analysis of travel decision learning in ...

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1st IEEE International Conference on Digital Twins and Parallel Intelligence, DTPI 2021

作者： Guo, Miao Ye, Peijun Liu, Xudong Liu, Sheng Xiong, Gang Zhang, Liguo Institute of Automation Chinese Academy of Sciences The State Key Laboratory of Management and Control for Complex Systems Beijing China Faculty of Information and Technology Beijing University of Technology Beijing China The Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing China The Guangdong Engineering Research Center of 3D Printing and Intelligent Manufacturing The Cloud Computing Center Chinese Academy of Sciences Beijing China

In the few decades, the rise of Internet and social media has fundamentally changed the management, control, and operation modes of modern engineering and social systems like defense, energy, critical health care and ... 详细信息

ISBN: (纸本)9781665433372

关键词： Deep learning Social networking (online) Scalability Perturbation methods Neurons Transportation Transforms

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Application of three-dimensional vision perception technology to industrial robots

Application of three-dimensional vision perception technolog...

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2021 Guangdong-Hong Kong-Macao Greater Bay Area Artificial Intelligence and Big Data Forum, AIBDF 2021

作者： Yang, Rui Mo, Qinglong Li, Yuhong Gan, Lin Hu, Ruihan Guangdong Institute of Intelligent Manufacturing Guangdong Key Laboratory of Modern Control Technology Guangzhou510070 China Cloud Computing Center Chinese Academy of Sciences Dongguan523808 China Guangdong Key Laboratory of Modern Control Technology Guangdong Institute of Intelligent Manufacturing Guangzhou China Engineering Research Center of Intelligence Perception and Autonomous Control Ministry of Education Beijing China Xinjiang Production and Construction Corps Key Laboratory of Modern Agricultural Machinery Shihezi University Shihezi China

The three-dimensional vision system can improve the active perception ability of the robot, and then guide its flexible operation. This system has been widely used in industrial production processes, such as disorderly sorting, assembly, flexible welding, and defect detection. In sorting, assembly and other applications, accurate perception in a complex and changeable industrial environment is essential. Moreover, the control and other operations should be completed under the guidance of feedback information based on the collected three-dimensional perception results. Nonetheless, improvements are still required, such as accurate three-dimensional detection and positioning of work-in-progress and autonomous guidance in a complicated industrial context with continuous changes. © 2021 Institute of Physics Publishing. All rights reserved.

关键词： Industrial robots

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