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

共 35215 条记录，以下是191-200 订阅

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Task Offloading Strategy in Multi-UAV Mobile Edge Computing via Deep Reinforcement Learning

Task Offloading Strategy in Multi-UAV Mobile Edge Computing ...

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

作者： Zonghui Chen Huahu Xu Chen Cheng School of Computer Engineering and Science Shanghai University Shanghai China

ISBN: (数字)9798331533113

ISBN: (纸本)9798331533120

Unmanned Aerial Vehicles (UAVs) serve as a powerful supplement to Mobile Edge Computing (MEC) systems, offering exceptional flexibility and mobility, which enable rapid deployment and the ability to adapt to rapidly changing demands. However, in this dynamic environment, existing research has not adequately considered the impact of user mobility and edge server load on task offloading performance. To address this gap, this paper proposes a task offloading algorithm based on Deep Deterministic Policy Gradient (DDPG), aiming to minimize the total system energy consumption and delay caused by computation offloading under limited system resources. Furthermore, to solve the load balancing issue among UAVs, this paper introduces a task migration mechanism, which further enhances task offloading efficiency. simulation results demonstrate that the proposed strategy effectively optimizes overall delay and energy consumption under resource-constrained conditions, while also achieving load balancing.

关键词： Energy consumption Multi-access edge computing Computational modeling simulation Load management Autonomous aerial vehicles Delays Servers Vehicle dynamics Load modeling

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modeling the Transportation Impact of Cycle Highways: A Case Study for Leipzig, Germany 16

Modeling the Transportation Impact of Cycle Highways: A Case...

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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： Meinhardt, Simon Bartholdtsen, Hans-Karl Nagel, Kai Technische Universität Berlin Department of Transport Systems Planning and Transport Telematics Straße des 17. Juni 135 Berlin 10623 Germany Technische Universität Berlin Straße des 17. Juni 135 Berlin 10623 Germany

The presented study implements five cycle highways into a transport model for the city of Leipzig, Germany. For the model, the open-source framework Multi-Agent Transport simulation (MATSim) is used. Additionally to a base case without cycle highways, the five cycle highways are simulated with three different cycling speed setups: 15 km/h, 25 km/h and 1500 km/h (as a potential analysis). With increasing cycling speed, an increased modal share of transport mode bike is observed (max. increase: 12%). Compared to their respective trips in the base case, agents achieve travel time gains of up to five minutes. The trips, which use the cycle highways mainly are trips with origin/destination rather close to the cycle highways. This euclidean distance also increases with increasing cycling speed on the cycle highways. This study predicts traffic volumes in the same range as those predicted by a feasibility study for one of the cycle highways, specifically within the inner-city area. © 2025 Elsevier B.V.. All rights reserved.

关键词： Agent-based Transport simulation bicycle traffic cycle highways sustainable transport

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Stochastic modeling of Path Length Dynamics in Ethereum’s Merkle Patricia Tries 19th

Stochastic Modeling of Path Length Dynamics in Ethereum’s M...

引用

19th international conference on Mathematical modeling and simulation of Systems, MODS 2024

作者： Kuznetsov, Oleksandr Kuznetsova, Kateryna Yezhov, Anton Chernushevych, Valentyn Zpoken OU Harju Maakond Tallinn Kesklinna linnaosa Sakala tn 7-2 Tallinn10141 Estonia Department of Theoretical and Applied Sciences eCampus University Via Isimbardi 10 CO Novedrate22060 Italy Department of Information and Communication Systems Security School of Computer Sciences V. N. Karazin Kharkiv National University 4 Svobody Sq. Kharkiv61022 Ukraine

ISBN: (纸本)9783031907340

This study presents a novel probabilistic framework for analyzing path length distributions in Merkle Patricia Tries, the foundational data structure of Ethereum’s state management system. We develop a mathematical model characterizing the probability distribution of path lengths for randomly generated Ethereum addresses and validate it through extensive computational simulations. Our findings reveal the logarithmic growth of average path lengths with respect to the number of addresses, confirming a critical property for Ethereum’s scalability. The study demonstrates remarkable accuracy in predicting average path lengths, with discrepancies between theoretical and empirical results remaining below 0.01 across tested scales from 1000 to 300 million addresses, encompassing Ethereum’s current state size. We identify and confirm the right-skewed nature of path length distributions, providing essential insights into worst-case scenarios and informing optimization strategies. Statistical analysis, including chi-square goodness-of-fit tests, strongly supports the model’s accuracy. This research bridges a significant gap between theoretical computer science and practical blockchain engineering, offering immediate applications for Ethereum client optimization, stateless client development, and informed protocol upgrade decisions. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Size distribution

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Hybrid Routing and Energy Management for Performance Optimization in Mobile Ad-hoc Networks 2

Hybrid Routing and Energy Management for Performance Optimiz...

引用

2nd international conference on Machine Learning and Autonomous Systems, ICMLAS 2025

作者： Nirmala, B. Vijaya Francis Raj, J. Relin Krishnan, R. Santhana Lavanya, V. Pitchirani, A. Kumar, V. Vinoth PSNA College of Engineering and Technology Department of Information Technology Dindigul India Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Department of Electronics and Communication Engineering Chennai India SCAD College of Engineering and Technology Department of Electronics and Communication Engineering Cheranmahadevi India Velammal College of Engineering and Technology Department of Computer Science and Engineering Madurai India SCAD College of Engineering and Technology Department of Computer Science and Engineering Cheranmahadevi India Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Avadi Department of Electronics and Communication Engineering Chennai India

ISBN: (纸本)9798331505745

Mobile Ad-hoc Networks (MANETs) encounter challenges related to dynamic topologies, energy constraints, and link instability. To enhance performance, a hybrid model integrates Ad-hoc On-demand Multipath Distance Vector (AOMDV), Power-Efficient Gathering in Sensor Information System (PEGASIS), and Deep Q-Network (DQN). OMNeT++, a discrete event simulation framework, facilitates comprehensive data collection, capturing key network parameters such as node density, signal strength, packet transmission rate, residual energy, routing paths, link breakage frequency, and packet delivery status. Stored in scalar and vector files, the dataset enables energy-efficient communication modeling and adaptive routing optimization. Data preprocessing involves cleaning, normalizing, and handling missing values using interpolation techniques while filtering noisy data through a sliding window averaging method. Feature extraction focuses on hop count, queue length, residual energy, and link expiration time, ensuring consistency and facilitating faster convergence. The hybrid model architecture integrates AOMDV for reliable multipath routing, PEGASIS for energy-efficient communication, and DQN for adaptive path optimization. simulation results indicate a 15% improvement in throughput, a 10% rise in packet delivery ratio, a 20% reduction in end-to-end delay, and a 30% decrease in average energy consumption. Applications extend to military operations, disaster recovery, vehicular networks, IoT sensor networks, and smart city infrastructure, ensuring efficient and adaptive communication. © 2025 IEEE.

关键词： Vehicular ad hoc networks

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AI-Assisted Data modeling and High-Resolution Image Synthesis: An Interactive Framework with Latent Diffusion Model Visualization

AI-Assisted Data Modeling and High-Resolution Image Synthesi...

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Intelligent Control, Computing and Communications (IC3), international conference on

作者： Asha Rani Borah Archana K. Pushpa Rani Sajjad Ziara Sorabh Lakhanpal Chalasanvi Vidyadhari Department of Computer Science Engineering New Horizon College of Engineering Bangalore India Department of Electrical Electronics & Communication Engineering Galgotias university Gerater Noida Uttar Pradesh Department of Computer Science and Engineering MLR Institute of Technology Hyderabad Telangana India Radiology Techniques Department College of Medical Technology The Islamic University Najaf Iraq Lovely Professional University Phagwara Punjab India Department of Information Technology GRIET Bachupally Hyderabad Telangana India

ISBN: (数字)9798331527495

ISBN: (纸本)9798331527501

In this research paper, we present the design and implementation of an AI assisted interactive framework for data modeling and high resolution image synthesis that leverages both state of the art latent diffusion models and visualisation of the real-time algorithm. The system proposed enables user to be able to better understand complex data modeling processes and creates high resolution images in the latent space using diffusion. The framework is both interactive, allowing modifications in parameters and real time visualization of change, making it a useful tool both for educational and for advanced AI research. In this paper, we also discuss the underpinning AI-assisted data modeling algorithms, and why they enable efficient data manipulation as well as high quality image synthesis then provide simulation results and practical applications to illustrate the capabilities of the framework of visualizing the latent diffusion process and generating high resolution images.

关键词： Image resolution Image synthesis Computational modeling simulation Data visualization Streaming media Diffusion models Real-time systems Data models Artificial intelligence

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modeling and simulation of Induction Heating Litz Coil Based on the Litz Wire Loss Model

Modeling and Simulation of Induction Heating Litz Coil Based...

引用

Power Electronics, computer Applications (ICPECA), IEEE international conference on

作者： Shaoze Wang Chengbin Zhu Jun Lei Yunfeng Wang Long Li Yan Shi School of Electronic Engineering Xidian University Xi'an China GD Midea Small Domestic Appliances Division Foshan China

ISBN: (数字)9798331533694

ISBN: (纸本)9798331533700

The Litz wire is extensively utilized in the applications of induction heating and wireless power transfer due to its small alternating current (AC) resistance and low loss at high frequency. However, the accurate numerical simulation of Litz wire consumes tremendous computational resources and time owing to its intricate structure of multi-strand twisted in multiple levels, thus posing huge challenges for its design and optimization. To tackle this issue, this study proposes a semi analytical full wave method to highly efficiently simulate the Litz wire. As a demonstration, a planar spiral coil of the induction cooker is simulated and measured. The simulation results demonstrate strong consistency with the measurement, verifying the correctness and effectiveness of the proposed modelling approach.

关键词： Coils Resistance Spirals Power measurement simulation Windings Wireless power transfer Conductivity Wire Induction heating

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A Combined GAN and DF Based Expansion and Prediction for Small Sample Data 16th

A Combined GAN and DF Based Expansion and Prediction for Sma...

引用

16th international conference on Modelling, Identification and Control, ICMIC 2024

作者： Wang, Li Lu, Junfeng Feng, Shanfang Wang, Xiaoyi Jin, Xuebo Yu, Jiabin Bai, Yuting Beijing Laboratory for Intelligent Environmental Protection School of Computer and Artificial Intelligence Beijing Technology and Business University Beijing100048 China

ISBN: (纸本)9789819617760

The high cost and difficulty of data collection result in discrete intermittency and limited available data for most datasets, posing challenges to modeling and prediction needs. Thus, it is crucial to explore methodologies suitable for discrete small sample data. Concurrently, unsupervised learning methods are employed for small sample prediction to circumvent the issue of low prediction accuracy resulting from inadequate a priori knowledge. Current data modeling and prediction methods rely heavily on neural network deep learning models, which are mainly designed for continuous processes and show low accuracy for intermittent processes. This paper proposes a data expansion method based on Time Generative Adversarial Networks (TimeGAN) and a prediction method based on the combination of Generative Adversarial Networks (GAN) and Deep Forest (DF). Firstly, the TimeGAN model is proposed to learn small sample data for data expansion. Then, the GAN-DF model is constructed so that the model is used for data prediction of unsupervised discrete processes. On this basis, we introduce the DFGAN and LSTM-DFGAN models, which embed DF and LSTM-DF models as generators within the GAN framework to enhance prediction accuracy for small sample data. simulation validation using contaminant data from a food processing process demonstrates the efficacy of the TimeGAN method in data expansion. The results demonstrate that the TimeGAN method is capable of effectively expanding the data, while the LSTM-DFGAN model exhibits the most optimal combined prediction effect. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Generative adversarial networks

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Virtual Prototype Study of a Boom-Type Offshore Transmission for Wind Power Operations and Maintenance

Virtual Prototype Study of a Boom-Type Offshore Transmission...

引用

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

作者： Tibing Xiao Yue Zhou Zheng Yang School of Electro-mechanical Engineering Guangdong University of Technology Guangzhou Guangdong P. R. China

ISBN: (数字)9798331533113

ISBN: (纸本)9798331533120

In order to solve the safety problems of non-contact operation and personnel transfer between operation and maintenance vessels and offshore wind turbines, a boom structure of the jib type offshore transmission device with a lift and sink compensation function is proposed. This paper takes the offshore transmission device and the six-degree-of-freedom motion platform as the research object, bases on the method of software co-simulation, uses Simcenter 3D motion to build its dynamics modelling, simulates the lifting and sinking motion caused by the waves in MATLAB, and then transfers it to the hydraulic system established by AMESim through the interface module to carry out the solution, so as to complete the virtual prototype design and simulation of the offshore transmission device. The simulation results show that the transmission device can substantially reduce the influence of waves on its motion under the effect of rise and sink compensation, which provides a theoretical basis for its physical model and an idea for the simulation of other complex electromechanical-hydraulic systems.

关键词： Solid modeling Three-dimensional displays simulation Prototypes Hydraulic systems Mathematical models Software Maintenance MATLAB Periodic structures

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Real-Time simulation of Complex 4D Wind Fields and Gusts for UAS Control System Development

Real-Time Simulation of Complex 4D Wind Fields and Gusts for...

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international conference on Unmanned Aircraft Systems (ICUAS)

作者： Surabhi Parab Artur Wolek Dipankar Maity Andrew Willis Electrical and Computer Engineering Charlotte NC USA Mechanical Engineering and Engineering Science University of North Carolina at Charlotte Charlotte NC USA

ISBN: (数字)9798331513283

ISBN: (纸本)9798331513290

This article describes a new suite of simulation plugins for the Gazebo 3D simulator to facilitate realistic simulation of time-varying 3D wind fields and gusts. The plugins integrate with ROS and Pixhawk PX4 Software-In-The-Loop (SITL) firmware to aid in the development of robust UAS control systems. Our approach features two main components: (1) real-time plugins for simulating environmental and sensed versions of complex, spatially varying wind velocity fields, using a Fourier-based compression of large CFD datasets, and (2) real-time plugins for modeling environmental and sensed versions of short-duration windblasts. By building on opensource Gazebo and ROS software, the developed framework provides high-accuracy physics simulation with support for multiple vehicles, fostering improved flight controller design and testing in cluttered or challenging atmospheric conditions.

关键词： Three-dimensional displays Atmospheric modeling Wind speed Urban areas Control systems Aerodynamics Real-time systems Vehicle dynamics Time-varying systems Testing

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Analysis of Defects' Impact on the External Magnetic Field of the Turbogenerator

Analysis of Defects' Impact on the External Magnetic Field o...

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international Youth conference on Radio Electronics, Electrical and Power Engineering (REEPE)

作者： Ekaterina P. Kurbatova Alexandr A. Kostenko Evgeniy D. Smirnov Anna V. Dyshina National Research University “MPEI” Moscow Russian Federation

ISBN: (数字)9798331531836

ISBN: (纸本)9798331531843

This paper presents an approach to monitoring the technical state of turbogenerator based on the control of an external magnetic field. The study had been performed for the synchronous turbogenerator T3F-160 and includes computer modeling and using neural networks. The effects of defects in form of winding current asymmetry and tooth fracture in the magnetic core, are examined. simulation results demonstrate the feasibility of defect identification through deviations in the magnetic flux density distribution. Based on the obtained data, a neural network was developed to classify machine states with defect-specific accuracy. The proposed method enhances the reliability of diagnostics and fault prediction, enabling integration into existing monitoring systems.

关键词： Solid modeling Computational modeling Magnetic cores computer network reliability Neural networks Windings Turbogenerators Stator windings Magnetic fields Monitoring

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