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检索条件"任意字段=Conference on Simulation-Driven Modeling and Optimization"

共 1170 条记录，以下是321-330 订阅

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A simulation-optimization Model for Automated Parcel Lockers Network Design in Urban Scenarios in Pamplona (Spain), Zakopane, and Krakow (Poland) 22

A Simulation-Optimization Model for Automated Parcel Lockers...

引用

Proceedings of the Winter simulation conference

作者： Bartosz Sawik Adrian Serrano-Hernandez Aitor Ballano Javier Faulin Department of Business Informatics and Engineering Management AGH University of Science and Technology Krakow POLAND Institute of Smart Cities Department of Statistics Computer Science and Mathematics Public University of Navarre Pamplona SPAIN

The constant rise of e-commerce coupled with extremely fast deliveries is a significant contributor to saturate city centers' mobility. To address this issue, the development of a convenient Automated Parcel Lockers (APLs) network improves last-mile distribution by reducing the number of transportation vehicles, the distances driven, and the delivery stops. This article aims to define and compare APL networks in the cities of Pamplona (Spain), Zakopane and Krakow (Poland). Thereby, a bi-criteria weighted-sum simulation optimization model is developed for a representative year for the aforementioned cities. The simulation forecasts the e-commerce demands whereas the optimal APL network is obtained with a bi-criteria maximum APL revenues and minimum network costs. Meaningful results are obtained from the multi-criteria hybrid model outcomes as well as from the cities comparison. These outcomes suggest efficient APLs networks considering cultural and demographic factors for a massive use of APLs in high-demand periods.

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modeling and optimization of Deploying Anti-UAV Swarm Detection Systems Based on the Mixed Genetic and Monte Carlo Algorithm

Modeling and Optimization of Deploying Anti-UAV Swarm Detect...

引用

2021 IEEE International conference on Unmanned Systems, ICUS 2021

作者： Yan, Jiading Xie, Haibin Li, Jie College of Intelligence Science and Technology National University of Defense Technology Changsha China

ISBN: (纸本)9780738146577

Focusing on detecting anti-UAV swarms, the study on the optimal deployment of detection systems is conducted in this paper. Firstly, it analyzes the problem of detecting anti-UAV swarms to decide feasible detection systems, to rasterizes the deployment space, and then select the deployment strategies. Secondly, based on typical early warning models and using segmented modeling methods, a detection model based on radar/photoelectric detection system is established. The optimization sub-objectives of each stage are sorted and quantified to meet the requirement of different detection stages, and an effectiveness evaluation model of detection system deployment for anti-UAV swarms is proposed. Thirdly, a mixed Genetic Algorithm and Monte Carlo algorithm (hereinafter 'GA-MCA') is put forward to solve the optimization problem of deploying the anti-UAV swarm detection system and then try to find out the best deployment plan of the detection system. Finally, a typical deployment case is designed, and the detection effectiveness of the mixed GA-MCA in different drone scales is evaluated. The simulation results show that compared with the traditional algorithm driven by mathematical models, the detection effectiveness of the deployment plan, which is based on the data-driven mixed GA-MCA, is increased by about 38.2%, which verifies the effectiveness of the mixed algorithm applied to the deployment optimization of the anti-UAV swarm detection systems. © 2021 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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A Flexible Multi-Agent Systems Task Environment for Simulating Hybrid Intelligence

A Flexible Multi-Agent Systems Task Environment for Simulati...

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International IEEE conference on Intelligent Systems, IS

作者： Benjamin Schlup Andrea Corradini Itopia ag –corporate information technology Zurich Switzerland MCI –Management Center Innsbruck Innsbruck Austria

ISBN: (数字)9798350350982

ISBN: (纸本)9798350350999

Hybrid Intelligence (HI) attempts to address and solve cognition-intensive tasks by combining Artificial Intelligence (AI) with human intelligence. Due to the novelty of the HI concept, there are few proven patterns for the optimal design of a Hybrid Intelligent System (HIS). To facilitate HIS simulations, we propose a framework to describe and simulate complex tasks in a multi-agent system. The tasks are solved collaboratively by teams of agents, simulating characteristics of actors with human or artificial intelligence. The prototype of a specification-driven task environment was evaluated using two sample applications. The results confirmed the strengths of the concept with regard to the study of different team constellations and cooperation patterns. Extensions would allow modelling of scenarios with higher complexity and more realistic simulation of human behaviors.

关键词： Analytical models Computational modeling Prototypes Collaboration Complexity theory Task analysis Hybrid intelligent systems optimization Multi-agent systems Testing

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A combined discrete-continuous model for railgun simulation

A combined discrete-continuous model for railgun simulation

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Pulsed Power conference, International conference on High-Power Particle Beams and International Symposium on Electromagnetic Launch Technology (EAPPC/BEAMS/EML), Euro-Asian

作者： Irene Ndindabahizi Tom Vancaeyzeele Johan Gallant Ben Lauwens Markus Schneider Department of Weapon Systems and Ballistics Royal Military Academy Belgium Brussels Belgium Department of Mathematics Royal Military Academy Belgium Brussels Belgium Electromagnetic Acceleration Group French-German Research Institute Saint Louis France

ISBN: (数字)9789038661353

ISBN: (纸本)9798350352733

Railgun weapon systems can accelerate projectiles to hypervelocities. Even though they are still at prototype stage, the feasibility of fitting a ship with such weapon system is an ongoing *** the limited power supply on board of ships, research efforts have been put in maximizing the efficiency of such weapon system against incoming missiles while minimizing the energy *** conduct such optimisation studies, we rely heavily on computer simulated scenarios which are greedy in simulation time. For accurate modeling of parameters’ influence on weapon lethality and energy consumption, it becomes a necessity to simulate the complete projectile path from the acceleration in the railgun to its end of trajectory at target engagement and damage assessment. The nature of the complex physics involved in such simulations requires the modeling of the interaction of processes which can be represented by continuous time and discrete event *** paper presents a computational framework which models the interaction of the processes during projectile acceleration in the railgun. It is computationally efficient to use a modular event driven environment where the different processes can interact. These processes can then be solved at different time scales with different numerical methods. The models are implemented using ConcurrentSim, which is a discrete event package in Julia that manages the scheduling of the *** presented model is validated using data from a Distributed-Energy-Supply (DES) railgun. Parameters for a non DES railgun configuration (breech-fed) are then determined to meet the performance of the DES railgun used for validation. The energy supply for both railguns is generated by the discharge of capacitors banks.

关键词： Projectiles Computational modeling Railguns Mathematical models Data models Numerical models Trajectory Marine vehicles optimization System analysis and design

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An EV-Traction Inverter Data-driven Modelling for Digital Twin Development

An EV-Traction Inverter Data-Driven Modelling for Digital Tw...

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International Scientific conference on Electric Power Engineering (EPE)

作者： Mahmoud Ibrahim Hadi Ashraf Raja Anton Rassõlkin Toomas Vaimann Ants Kallaste Department of Electrical Power Engineering and Mechatronics Tallinn University of Technology Tallinn Estonia

Digital Twin (DT) technology has achieved a significant breakthrough in the development of numerous applications, including electric vehicles (EVs). This technique involves the creation of a virtual version of a real object, utilizing simulation and optimization tools with real data to optimize its functioning. The traction inverter is considered the brain of the EV drive system, as it controls the power flow between the battery and the electric motor. It converts the DC voltage from the battery into AC voltage and adjusts the frequency and amplitude to control the speed and torque of the motor. This research work presents the DT modelling procedures of an EV traction inverter. The basic principles of DT are discussed, and the model-driven DT modelling technique is compared to the data-driven. The motor-drive physical model (test bench) is provided. A data-driven model of the inverter was generated using a nonlinear regression-based artificial neural network ANN. Historical data from experimental tests were used as a modeling reference. The obtained results from the data-driven model achieved high prediction accuracy.

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Simulating the Co-Evolution of Porous Microstructures and Grain Growth in Sintered Ag Die Attach Layers

Simulating the Co-Evolution of Porous Microstructures and Gr...

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Thermal, Mechanical and Multiphysics simulation and Experiments in Micro-Electronics and Micro-Systems EuroSimE

作者： Xiao Hu Jianlin Huang René Poelma Hans van Rijckevorsel Willem Dirk van Driel Guoqi Zhang Department of Microelectronics Delft University of Technology Delft The Netherlands Ampleon B.V. Nijmegen The Netherlands Nexperia Nijmegen The Netherlands

ISBN: (数字)9798350393002

ISBN: (纸本)9798350393019

In this study, we introduced a hybrid Potts-phase field model to simulate the co-evolution of grain growth and pores migration in sintered silver layers. The Potts model is good at capture the grain growth dynamics, while the phase field model describes the evolution of the porous network. These models are coupled via a hybrid free energy function to achieve a realistic representation of the microstructure evolution. This study further extends the hybrid model by incorporating (a) a flexible exchange interaction matrix to model the crystal anisotropy in grain growth, (b) Glauber or Kawasaki dynamics to describe different diffusion mechanisms, and (c) the effect of pinning sites, representing impurity-driven grain boundary stabilization. The computational framework is implemented using Taichi Lang, which allows for efficient parallel simulations. Results show that the model effectively captures the long-term evolution of the sintered silver microstructure in good agreement with experimental observations. This hybrid model is a powerful tool to predict microstructural reliability of sintered silver die attach layers, supporting material design and process optimization for high-power electronic applications.

关键词： Grain boundaries Silver Computational modeling Data models Computational efficiency Microstructure Thermal stresses optimization Stress Microassembly

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Two-Stage Trajectory optimization for Flapping Flight with Data-driven Models

Two-Stage Trajectory Optimization for Flapping Flight with D...

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IEEE International conference on Robotics and Automation (ICRA)

作者： Hoff, Jonathan Kim, Joohyung Univ Illinois Coordinated Sci Lab Urbana IL 61801 USA Univ Illinois Dept Elect & Comp Engn Urbana IL 61801 USA

ISBN: (纸本)9781728190778

Underactuated robots often require involved routines for trajectory planning due to their complex dynamics. Flapping-wing aerial vehicles have unsteady aerodynamics and periodic gaits that complicate the planning procedure. In this paper, we improve upon existing methods for flight planning by introducing a two-stage optimization routine to plan flapping flight trajectories. The first stage solves a trajectory optimization problem with a data-driven fixed-wing approximation model trained with experimental flight data. The solution to this is used as the initial guess for a second stage optimization using a flapping-wing model trained with the same flight data. We demonstrate the effectiveness of this approach with a bat robot in both simulation and experimental flight results. The speed of convergence, the dependency on the initial guess, and the quality of the solution are improved, and the robot is able to track the optimized trajectory of a dive maneuver.

关键词： Trajectory planning Computational modeling conferences Aerodynamics Data models Planning Vehicle dynamics

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Real Time Load Estimation and Graph-Based Modelling for Load Shedding in Rural DSO Digital Twin Frameworks: A Case Study from NE Spain

Real Time Load Estimation and Graph-Based Modelling for Load...

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IEEE PES Innovative Smart Grid Technologies conference Europe (ISGT Europe)

作者： Ignacio Glenny-Crende Francesca Rossi Vinicius A. Lacerda Eduardo Prieto-Araujo Yolanda Castellón-Lalanza Eng. Department & CITCEA-UPC iGrid T&D & UPC-BarcelonaTech Barcelona Spain CITCEA-UPC UPC BarcelonaTech Barcelona Spain Eng. Department iGrid T&D Barcelona Spain

ISBN: (数字)9798350390421

ISBN: (纸本)9798350390438

The electrification of energy demand and the challenges associated with the energy transition pose significant uncertainties for rural distribution system operators (DSOs). Digital twin (DT) frameworks can provide real-time analysis, modeling, and simulation capabilities. However, traditional DT applications rely heavily on data, presenting challenges for rural DSOs with limited monitoring coverage and constrained data availability. The proposed load shedding application combines the DT framework’s data-driven load estimation and graphbased grid modeling offering operator assistance in reduced data availability scenarios. This is exemplified with a case study using data from a North-Eastern Spain Rural DSO.

关键词： Analytical models Sequential analysis Europe Estimation Switches Load shedding Real-time systems Digital twins optimization Load modeling

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Optimizing Latency and Communication in Federated Edge Computing with LAFEO and Gradient Compression for Real-Time Edge Analytics

Optimizing Latency and Communication in Federated Edge Compu...

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Mobile Computing and Sustainable Informatics (ICMCSI), International conference on

作者： Namratha P Koushik Reddy Chaganti Sivananda Lahari Reddy. Elicherla Surekha Guddati Akarapu Swarna P. Thiramal Reddy Department of CSE ATES Institute of Technology and Science Anantapur Dept. of Computer and Information Systems University of the Cumberlands KY USA Dept of CSE Dayananda Sagar University Bangalore Dept of CSE Vidya Jyothi Institute of Technology Hyderabad Dept of CSE Vignan Institute of Technology and Science Hyderabad

ISBN: (数字)9798331522667

ISBN: (纸本)9798331522674

The increasing need for real-time data analytics in edge computing is furthered by the latency pressures from computational and communication bottlenecks, thus demanding novel solutions. Fundamental approaches to federated learning and distributed machine learning do not accommodate changes in dynamic latency conditions very well, thereby being inefficient in terms of synchronization, communication overhead, and delay in task execution. This paper presents a holistic framework consisting of three innovative approaches to solve these problems: Latency-Aware Federated Edge-Aware optimization (LAFEO), Latency-driven Gradient Compression with Adaptive Sparsity (LAGCAS), and Predictive Latency Compensation with Dynamic Replication (PLCDR). The LAFEO framework consists of a double-layer optimization framework, combining latency-weighted scheduling with reinforcement learning to dynamically adapt the synchronization frequencies. This results in 25-30% end-to-end latency reduction with an accuracy deviation that is capped at 2% centralized models. LAGCAS reduces communication overhead by applying adaptive gradient scarification methods, bringing compressions of gradients under real-time accuracy thresholds: it reduces 40% communication volume and accelerates convergence by 20%. PLCDR uses predictive modelling to predict latency bottlenecks and dynamically replicates critical computations across the edge nodes. It hence offers 15-25% decrease in the completion time of tasks and up to 30% enhancement in the resilience of system sets. The existing methods will be addressed with the key limitations due to the introduction of latency-aware mechanisms that adapt to real-time edge conditions along with high accuracy and efficiency. simulation results have shown marked scalability improvements, latency reductions, and resilience; in its positioning, this work's effort is a transformative advancement in the latency-sensitive edge computing process.

关键词： Adaptation models Accuracy Computational modeling simulation Scalability Real-time systems Synchronization optimization Edge computing Resilience

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Proceedings of the Platform for Advanced Scientific Computing conference, PASC 2021

Proceedings of the Platform for Advanced Scientific Computin...

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2021 Platform for Advanced Scientific Computing conference, PASC 2021

ISBN: (纸本)9781450385633

The proceedings contain 17 papers. The topics discussed include: ensuring statistical reproducibility of ocean model simulations in the age of hybrid computing;simulation of droplet dispersion in COVID-19 type pandemics on Fugaku;refactoring the MPS/university of Chicago radiative MHD (MURaM) model for GPU/CPU performance portability using OpenACC directives;stream-AI-MD: streaming AI-driven adaptive molecular simulations for heterogeneous computing platforms;performance optimization and load-balancing modeling for superparametrization by 3D LES;progress towards accelerating the unified model on hybrid multi-core systems;in-situ assessment of device-side compute work for dynamic load balancing in a GPU-accelerated PIC code;and fast scalable implicit solver with convergence of equation-based modeling and data-driven learning: earthquake city simulation on low-order unstructured finite element.

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