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检索条件"任意字段=International Conference on Computer Modeling and Simulation"

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Evaluating truck-to-rail mode shift for freight decarbonization in major U.S. transportation hubs with varying urban forms 16

Evaluating truck-to-rail mode shift for freight decarbonizat...

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16th international conference on Ambient Systems, Networks and Technologies Networks, ANT 2025 / 8th international conference on Emerging Data and Industry 4.0, EDI40 2025

作者： Ismael, Abdelrahman Zuniga-Garcia, Natalia Uhm, Hyun-Seop Shen, Hui Sahin, Olcay Auld, Joshua Mohammadian, Abolfazl Argonne National Laboratory 9700 S. Cass Ave Lemont 64539 IL United States University of Illinois Chicago 1200 W Harrison St Chicago 60607 IL United States

This research explores the impacts of increasing rail freight's role in major U.S. transportation hubs with different urban forms to reduce greenhouse gas emissions in the freight sector. Using the POLARIS agent-based simulation tool, the study compares three cities - Chicago, Atlanta, and Dallas-Fort Worth - representing varying degrees of density, centrality, and spread of their economic activities and rail network. The paper contributes by (1) providing a framework for modeling intermodal freight operations in the context of an agent-based simulation models, (2) evaluating how rail integration interacts with urban form, and (3) offering insights for policymakers to develop mode-shift strategies that account for urban disparities, promoting effective and equitable decarbonization policies. Principal findings show that shifting freight from trucks to rail significantly reduces trucks' vehicles miles traveled, with the greatest benefits in Chicago due to its dense, polycentric form and rail network, while Dallas-Fort Worth sees smaller impacts due to limited rail coverage and higher sprawl. Although Atlanta also shows centrality patterns, the limited rail network limits the benefits of mode shift policies. These results highlight the influence of urban form and rail station density on the effectiveness of trucks to rail mode shift policies. © 2025 Elsevier B.V.. All rights reserved.

关键词： agent-based simulation freight intermodal rail trucks

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Research on Numerical Integration Methods Based on LC Binary Equivalent Switch Model in Real-Time simulation of Power Electronic System 8th

Research on Numerical Integration Methods Based on LC Binary...

引用

8th international conference on Life System modeling and simulation, LSMS 2024 and 8th international conference on Intelligent Computing for Sustainable Energy and Environment, ICSEE 2024

作者： Liang, Bowen Chen, Guochu School of Electrical Engineering Shanghai Dianji University Shanghai China

ISBN: (纸本)9789819602247

In real-time simulation of power electronic system, the modeling method and numerical integration method are key factors affecting simulation performance. The LC binary method significantly reduces hardware resource utilization and FPGA workload. However, different integration methods have varying error accuracy and convergence. This paper provides a detailed analysis of the impact of different numerical integration methods on the system and proposes an effective and versatile real-time simulation method for multi-switch circuit, demonstrated through the application case of a single-phase inverter based on LC filtering. Comparative tests with Simulink model under a real-time simulation step size of 1μs show that the proposed method achieves a relative error of less than ± 1% and consumes hardware resources by no more than 30%. This approach demonstrates practical value for efficient real-time simulation of multi-switch power electronic system. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： LC Binary Equivalent Switch Model Numerical Integration Method Real-Time simulation

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modeling and simulation of Grid-Connected PV System Faults Using MATLAB/Simulink

Modeling and Simulation of Grid-Connected PV System Faults U...

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Learning and Technology conference (L&T)

作者： Mayar Alkhawaja Sandy Miguel Moutaz Abu Shabab Muhy Eddin Za’Ter Majd Ghazi Batarseh Electrical Engineering Department Princess Sumaya University for Technology Amman Jordan Now With the Electrical and Computer Engineering King Abdullah University of Science and Technology Saudia Arabia Now With the College of Engineering and Computer Science University of Central Florida Orlando USA Electrical and Computer Engineering University of Colorado Boulder Boulder USA

ISBN: (数字)9798331532215

ISBN: (纸本)9798331532222

Grid-connected photovoltaic (PV) systems are crucial to modern renewable energy strategies, but various types of faults can significantly impact their performance. Understanding the behavior of these faults is essential for improving system reliability and reducing maintenance costs. This paper investigates the impact of common faults, including open-circuit, short-circuit, partial shading, and grid faults, by simulating them using MATLAB/Simulink. The focus is on modeling faults that lead to power output reduction. The simulation results demonstrate how different fault types affect critical system parameters, such as grid voltage and active power output. The study highlights the value of simulation as a flexible approach for exploring fault scenarios, providing insights into fault detection and mitigation strategies that can help optimize PV system performance and support the development of robust fault data collection, detection, and classification techniques.

关键词： Renewable energy sources Costs Fault detection Prevention and mitigation System performance simulation Voltage Real-time systems Maintenance MATLAB

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Multi-agent simulation of Complex Economic Systems Driven by Deep Reinforcement Learning

Multi-agent Simulation of Complex Economic Systems Driven by...

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international conference on computer Research and Development (ICCRD)

作者： Bo Chen Shiqi Ding Yukun Lin Guohong Chen College of Computer and Data Science Fuzhou University Fuzhou China School of Economics and Management Fuzhou University Fuzhou China

ISBN: (数字)9798331531881

ISBN: (纸本)9798331531898

In economics, the study of macroeconomic laws often encounters challenges such as difficulties in data collection and low data quality. A complex economic system (CES) simulation model based on Multi-agent simulation (MAS) was designed and proposed to provide reliable, high-quality virtual data support for economic research to address these issues. To enhance the intelligence of agent behaviors in the simulation model, an economic agent decision-making model based on the Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithm was developed, and experimental results demonstrate the effectiveness of the TD3 algorithm in CES simulations. Additionally, the model's decision-making capability in complex economic environments was further improved by incorporating Long Short-term Memory (LSTM) networks to handle temporal relationships. The research presented herein explores the application effects of deep reinforcement learning in economic research, providing a reliable source of virtual economic data for theoretical economic research and offering new perspectives and methods for economic system simulation research.

关键词： Economics Computational modeling Decision making Reliability theory Deep reinforcement learning Reliability engineering Data models Systems simulation Long short term memory Research and development

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Using Machine Learning Algorithms in Edge Intelligence for Ultra-Reliable and Low-Latency Communications in the Industrial Metaverse

Using Machine Learning Algorithms in Edge Intelligence for U...

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international CSI computer conference, CSICC

作者： Reza Mohammadvand Naser Mozayani dept. Computer Engineering Iran University of Science and Technology Tehran Iran

ISBN: (数字)9798331523114

ISBN: (纸本)9798331523121

Given the rapid advancements in technologies such as the metaverse and digital twins, the need for effective integration of communication, computation, and storage in complex systems and edge computing environments is becoming increasingly apparent. This paper proposes an architecture to support an industrial metaverse based on digital twins that optimizes resources by leveraging mobile edge computing and ultra-reliable low-latency communication. This architecture reduces latency by employing task offloading and storage methods on nearby edge servers, meeting the precise requirements of future metaverses in terms of reliability and latency minimization. The proposed model, utilizing reinforcement learning algorithms such as Deep Q-Network (DQN), Double Deep Q-Network (DDQN), and Dueling Double Deep Q-Network (Dueling DDQN), is capable of achieving adaptability in dynamic conditions and making intelligent decisions. The simulation results demonstrate that the proposed method reduces by more than 10% on average compared to the best method available in the literature and improves resource utilization efficiency.

关键词： Metaverse Heuristic algorithms Computational modeling simulation computer architecture Artificial neural networks Ultra reliable low latency communication Digital twins Delays Optimization

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Joint Task Offloading and UAV Deployment for Collaborative HAP-UAV Systems

Joint Task Offloading and UAV Deployment for Collaborative H...

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Consumer Electronics and computer Engineering (ICCECE), 2021 IEEE international conference on

作者： Kun Wang Haotian Ma Luwei Fu Qinyong Li Zhiwei Zhao School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu China

ISBN: (数字)9798331533113

ISBN: (纸本)9798331533120

In emergency scenarios such as natural disasters, unmanned aerial vehicles (UAVs) are widely employed to provide communication and computation services when ground infrastructure fails. However, UAVs face limitations in resources. High Altitude Platforms (HAPs), operating in the stratosphere, offer a promising solution with their wide coverage and substantial payload capacity. This paper proposes a collaborative task offloading scheme that combines UAVs and HAPs to minimize task delays, considering task types and the mobility of ground devices, which are typically overlooked. We jointly optimize UAV deployment and task scheduling, modeling deployment as a maximum clique problem and task scheduling as a device-UAV matching problem solved by a stable matching algorithm. Numerical simulations demonstrate the effectiveness of the proposed solution.

关键词： Processor scheduling simulation Collaboration Terrestrial atmosphere Autonomous aerial vehicles Numerical simulation Scheduling Numerical models Delays Payloads

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Research on simulation Model of Urban Environment Design and Renewal Using Virtual Reality Technology

Research on Simulation Model of Urban Environment Design and...

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Electronics, Energy Systems and Power Engineering (EESPE), IEEE international conference on

作者： Wei Ma Changchun University of Architecture and Civil Engineering Changchun China

ISBN: (数字)9798350389579

ISBN: (纸本)9798350389586

This paper proposes a research method of urban environment design and renewal simulation model based on virtual reality technology, aiming to improve the efficiency and accuracy of urban planning and renewal process. This method takes point cloud data processing as the core technology, combines advanced 3D modeling and virtual reality technology, and constructs a high-precision urban environment simulation system. The system includes key modules such as data acquisition, optimization algorithm design, model construction, simulation verification and interactive operation. Among them, through the improved point cloud data processing algorithm, the rapid reconstruction of complex urban spatial structure is realized, and efficient 3D rendering and large-scale scene simulation are supported. Data analysis of multiple actual urban scenes shows that this method has excellent performance in various environments. The simulation system supports accurate visual comparison of different urban design schemes, interactive scene adjustment through real-time dynamic operation, and quantitative evaluation of design results. Experimental data show that the system can control the simulation error within 5% in multiple urban renewal scenarios; the data processing efficiency is improved by about 30% compared with traditional methods, and the 3D reconstruction time is shortened to 70% of the original.

关键词： Point cloud compression Solid modeling Accuracy Three-dimensional displays Heuristic algorithms Urban planning Virtual reality Data processing Rendering (computer graphics) Data models

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On the Application of a Queuing Network to Simulate Container Transshipment in a Sea Container Terminal 23rd

On the Application of a Queuing Network to Simulate Cont...

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23rd international conference on Information Technologies and Mathematical Modelling, ITMM 2024

作者： Kazakov, Alexander Lempert, Anna Vu, Giang Zharkov, Maxim Matrosov Institute for System Dynamics and Control Theory of Siberian Branch of Russian Academy of Sciences (IDSTU SB RAS) Irkutsk Russian Federation Irkutsk National Research Technical University Irkutsk Russian Federation

ISBN: (纸本)9783031883064

The article concerns mathematical modeling and simulation of container handling in a sea container terminal based on queueing theory. The model has the form of a queueing network (QN), and various request flows are applied to describe the arrival of transport from sea and land. QN nodes describe the operation of the terminal structural elements, so they differ in the types of queuing systems used, queue length, number of servicing channels, and their performance. To describe two container movement routes, we use different types of requests with individual route matrices. The object of the study is the largest sea container terminal in the northern part of Vietnam. The QN describing its operation includes 15 nodes, two types of requests, and two incoming flows, one of which is batch. Based on the results of the simulation, the current level of terminal load and its maximum throughput are determined. In addition, we assess the operability of the object when organizing a new route followed by ultra-large container vessels. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： container shipping mathematical model queuing theory sea transport simulation

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simulation of Cyber Physical Systems Using Modelica: Case of Master Side in Tactile Internet

Simulation of Cyber Physical Systems Using Modelica: Case of...

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IEEE SSD international Multi-conference on Systems, Signals and Devices

作者： Ahmed Haval Fattah Wrya Monnet Mechatronics Engineering Department Tishk International University Erbil Iraq Computer Science and Engineering University of Kurdistan-Hewler Erbil Iraq

ISBN: (数字)9798331542726

ISBN: (纸本)9798331542733

Cyber-physical systems combine computational, communication, and physical components. They are employed in many fields, such as manufacturing, transportation, and robotics. CPS's master side overseas, directs, and organizes the entire system. Usually, it provides instructions to actuators on a slave side which gathers information from sensors on the physical parts and sends them back to the master side to control the overall system behavior. Building a CPS system for research purposes is not a simple task, using simulations is a viable choice to explore the possibility and feasibility of such systems before building them. In this work, we suggest the utilization of the simulation tool Modelica to build the master side of a CPS system. This mainly consists of a haptic interface that can manipulate and intervene in a distant physical system, through the slave, while feeding back the force-torque information from the slave. Modelica's choice is based on this software's electromechanical simulation capability. The result of the work shows the utility and usefulness of the simulation tool to generate force signals for the remote end control while receiving torque feedback to simulate the kinesthetic feeling of a haptic interface.

关键词： Tactile Internet Torque Costs Object oriented modeling Computational modeling Buildings Force Cyber-physical systems Main-secondary Sensor systems

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A Conceptual Framework for Digital Twins of Multi-Agent Systems 16

A Conceptual Framework for Digital Twins of Multi-Agent Syst...

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16th international conference on Ambient Systems, Networks and Technologies Networks, ANT 2025 / 8th international conference on Emerging Data and Industry 4.0, EDI40 2025

作者： Lee, Hui Min Jamali, Ruhollah Lazarova-Molnar, Sanja Institute of Applied Informatics and Formal Description Methods Karlsruhe Institute of Technology Kaiserstr. 89 Karlsruhe 76133 Germany The Maersk Mc Kinney Moller Institute University of Southern Denmark Campusvej 55 Odense 5230 Denmark

Multi-agent Systems (MASs) are complex systems made up of agents that can be any entities with the ability to interact autonomously and make decentralized decision-making to solve complex problems. Data-driven Agent-based modeling and simulation (DDABMS) equips MASs with access to decisions based on near-real-time data, allowing for more informed decisions for systems' enhancements. Digital Twins (DTs) can further enhance MASs by serving as virtual replicas that enable what-if scenarios exploration and allow continuous validation and refinement of the underlying models with real-time data from MASs. However, we discovered a gap in systematically integrating DTs with DDABMS, as existing efforts focus on specific problems and domains rather than providing a generalized framework to develop DTs with DDABMS. This paper addresses this gap by proposing a generalized framework to develop DTs for MASs with DDABMS. To demonstrate the practicability of our proposed framework for modeling and simulation of complex systems, we present an illustrative case study based on an epidemiological Susceptible-Infected-Recovered model. © 2025 Elsevier B.V.. All rights reserved.

关键词： agent-based modeling data-driven agent-based modeling decision making digital twins multi-agent systems simulation

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