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Proceedings of the 2010 Spring simulation Multiconference

作者： Zhou, Ming Pan, Yanchun Chen, Zhimin Center for Systems Modeling and Simulation Indiana State University United States College of Management Shen Zhen University Shen Zhen China

ISBN: (纸本)9781450300698

Allocating storage space at TPL systems differs significantly from traditional private logistics systems. The resources are commodities sold directly to customers of different characteristics. Total revenue suffers when allocating too much to lower-rate (i.e. price sensitive) customers;and the resources allocated to full-rate (i.e. time sensitive) customers become "spoiled" when the orders do not arrive as expected. The random nature of order characteristics (including arrival pattern) makes allocation decisions very hard. This paper proposed a simulation approach that focuses on the development of a robust conceptual framework for simulation modeling and analysis of this important class of problems. Computer models are being developed with ARENA© and used to verify and validate the concepts and mechanisms developed. Limited simulation experiments were conducted to compare allocation strategies in terms of defined performance measures, and produced the results consistent with intuition and practice. © 2010 SCS.

关键词： Logistics

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modeling and simulation of storage space allocation at TPL systems

Modeling and simulation of storage space allocation at TPL s...

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Emerging M and S Applications in Industry and Academia Symposium, EAIA 2010

作者： Zhou, Ming Pan, Yanchun Chen, Zhimin Center for Systems Modeling and Simulation Indiana State University United States College of Management Shen Zhen University Shen Zhen P.R. China

关键词： Logistics

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Multi-Targets Visiting Orbit Design Based on Numerical Method

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Guidance,Navigation and Control 2025年第1期05卷 139-148页

作者： Zenan Zhong Zhengxiang Sun Songyan Wang Tao Chao Ming Yang Control and Simulation Center Harbin Institute of Technology National Key Laboratory of Modeling and Simulation for Complex Systems Harbin Institute of Technology Beijing Institute of Space Long March Vehicle

In this paper, for the two/three targets in the circle orbit with the same altitude, a numerical method is presented to design an orbit for a spacecraft to visit multiple targets without maneuvering. First,for the two targets' case, an equation is established by the relationship of the two angles that both are the function of the time, one of the angles is the angle between two targets' geocentric position vectors at two times, and another one is the spacecraft flight angle during the two times. The visit time can be solved by the assumption that one of the visit times is known in the equation, and the orbit element can be transferred from the position and velocity vector determined by the solved visit time. Then, for the three targets' case, the problem is decoupled into two cases of two targets, and there is a public target in each case. Based on the method for two targets, two different orbits can be obtained by determining the visit time of the public target. The difference between two orbits can be expressed by the difference in velocity vectors of the public target at different times. A sampling method is utilized to select two velocity vectors with relatively small differences as initial values, the Newton iteration method is used to obtain visit times with higher accuracy. simulation results illustrate the effectiveness of the orbit design methods.

关键词： Orbit design method multiple targets visit circle orbit non-maneuvering

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Defense System modeling and Effectiveness Evaluation Analysis Based on Kill Chain Model

Defense System Modeling and Effectiveness Evaluation Analysi...

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15th Asia Conference on Mechanical and Aerospace Engineering, ACMAE 2024

作者： Liu, Yuanshuai Li, Wei Chao, Tao National Key Laboratory of Modeling and Simulation for Complex Systems Harbin Institute of Technology Harbin150001 China

ISBN: (纸本)9781643685892

This paper addresses the interception mission of hypersonic vehicles by weapon defense systems. A simulation model of the attack-defense confrontation process is constructed based on the "F2T2EA" kill chain model. Building upon this framework, a novel method combining TOPSIS, the entropy weight method, and fuzzy theory is proposed, guided by the concept of kill chain closure, to evaluate the interception effectiveness of defense systems against boost-glide hypersonic vehicles. The model's effectiveness is verified through practical examples, with consistent conclusions obtained through traditional grey correlation analysis, thus confirming the feasibility and reliability of both the model and the evaluation methodology. The results of this research offer reliable technical support for the design and combat application of defense systems and provide a reference for future optimization efforts. © 2025 The Authors.

关键词： boost-glide vehicle grey correlation performance evaluation TOPSIS

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Defining "Good Enough" for modeling and simulation Verification and Validation

Defining "Good Enough" for Modeling and Simulation Verificat...

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AIAA Science and Technology Forum and Exposition, AIAA SciTech Forum 2025

作者： Ferguson, Ben Pratt Turner, Patricia L. Vander Wyst, Anton Systems Engineering Integration and Test Northrop Grumman Defense Systems RoyUT84067 United States Systems Modeling Simulation Northrop Grumman Mission Systems BaltimoreMD21240 United States Systems Engineering Northrop Grumman Aeronautics Systems MelbourneFL32935 United States

ISBN: (数字)9781624107238

ISBN: (纸本)9781624107238

When defining the need, developmental requirements, and expectations for a given model or simulation, how can the model owners, developers, users, and customers (a.k.a. stakeholders) know when the model has reached its expected potential? In other words, when is the Model and simulation (M&S) "good enough?" M&S stakeholders need to understand the end goal of the M&S effort to define scope and cost. Knowing what is good enough requires thinking about the definition of done before the M&S activities begin. Per the recommendations from studies by the Government Accountability Office (GAO), defining the intended use and scope early, with frequent check-ins from the customers, will reduce rework, scope creep and unintended/unneeded/unwanted fidelity required for the model’s intended use. By clearly answering design questions before implementation, the definition of done will be much clearer for the developers. This reduces swirl developers face when analyzing data to know if the model is good enough for its intended use. The tools and processes identified in this paper address government concerns in model development swirl, scope creep and cost overruns. © 2025, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： Sales

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Optimal Deployment of Target Localization With Distance-Dependent Noise

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IEEE Internet of Things Journal 2025年

作者： Tian, Junxi Yang, Ming Chao, Tao Harbin Institute of Technology Control and Simulation Center National Key Laboratory of Modeling and Simulation for Complex Systems Harbin150001 China

The cooperative localization of radio-based distance measurement is one of the methods to effectively suppress the nonline of sight (NLOS) ranging errors and as a complement to visual/global navigation satellite system (GNSS) localization for unmanned aerial vehicle (UAV) in GNSS challenging or denied environments due to its motility. Target localization can be regarded as a special case of cooperative localization. Meanwhile, the UAV can be considered as a ranging node when the ranging terminal is rigidly mounted on the UAV. To improve the target localization accuracy, the optimal deployment of anchor UAVs is one of the factors we consider when the noise characteristics are different. In this paper, the range-dependent noise in a real flight environment is considered and modeled separately according to the difference in noise characteristics. Subsequently, based on this correlation model, the Fisher information matrix (FIM) and a cost function derived from the A-optimal criterion are provided. Finally, the optimal deployment conditions and the minimum mean square error (MMSE) can be derived by minimizing the cost function as the objective. Through simulation and localization experiments, the validity of the optimal deployment conditions and the corresponding MMSE are verified. Meanwhile, it is concluded that when the noise is range-dependent, it will not affect the optimal deployment result but will significantly change the value of MMSE. © 2014 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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modeling and simulation of Saab Gripen's vehicle systems

Modeling and simulation of Saab Gripen's vehicle systems

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作者： Steinkellner, Sören Andersson, Henric Gavel, Hampus Krus, Petter Saab Aerosystems Linköping SE-58188 Sweden Linköpings Universitet Linköping SE-58183 Sweden Modeling and Simulation Vehicle Systems Dept. Sweden Methods and Tools Dept. Sweden Machine Design Dept. Sweden

ISBN: (纸本)9781563479786

This paper gives an overview of the modeling and simulation work for the military aircraft JAS 39 Gripen's vehicle systems. The vehicle systems comprise fuel, ECS, hydraulic, and auxiliary power systems and also landing gear. Vehicle systems have several modeling challenges such as both compressible air and less compressible fluids that give stiff differential equations, g-force effects, nonlinear cavitation and saturation. It is also a complex system of integrated systems that requires models with integrated system software. Dynamic models based on physical differential equations have generally been used. The physical systems were previously modeled in Easy5 and the software in MATRIXx. Changes in tools where the physical systems are modeled in Dymola and the control algorithms are modeled in Simulink have opened up for new possibilities for more advanced and more complete system simulations. simulations have been performed during the whole development cycle of the aircraft from concept evaluation to qualification tests. The paper gives some examples from the simulations where system performance and the internal states of the system are calculated. Copyright © 2009 by the American Institute of Aeronautics and Astronautics, Inc.

关键词： Nonlinear equations

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Dynamic-Aware and Static Context Network for large-scale 3D place recognition

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Knowledge-Based systems 2025年 319卷

作者： Liao, Ming Di, Xiaoguang Liu, Maozhen Lv, Teng Zhang, Xiaofei Zhu, Runwen Control and Simulation Center Harbin Institute of Technology Harbin150080 China National Key Laboratory of Modeling and Simulation for Complex Systems Harbin150080 China

3D point cloud-based place recognition enables robots to obtain precise global positions without GPS, correct trajectory drift in SLAM, and recover from the kidnapped robot problem. However, in outdoor environments, the presence of moving objects can cause occlusions in point clouds and introduce noise into the data, leading to localization failures. To address this issue, we propose a Dynamic-Aware and Static Context Network (DASC-Net) for large-scale 3D place recognition. Our approach leverages the spatio-temporal consistency of point cloud sequences to accurately segment dynamic objects while incorporating static point cloud context to compensate for feature loss caused by noise interference or occlusions from dynamic objects, thereby enhancing robustness and generalization. Specifically, DASC-Net adopts a two-stage strategy: first, it introduces a coarse-to-fine moving object segmentation method to effectively eliminate dynamic noise;second, it utilizes spatial context association and multi-scale feature aggregation to improve static feature representation and matching. Extensive experimental results demonstrate that DASC-Net outperforms existing place recognition approaches, particularly in dynamic scenes. © 2025

关键词： Image segmentation

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A Hybrid Approach for Multiclass Brain Tumor Classification: Ensemble Convolutional Neural Networks and PSO Optimization

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Traitement du Signal 2025年第2期42卷 813-823页

作者： Djemai, Mohamed Naimi, Hilal Bourennane, Mohammed Laboratory for Modeling Simulation and Optimization of Systems Complexes University of Djelfa Djelfa17000 Algeria Laboratory of Telecommunications and Smart Systems University of Djelfa Djelfa17000 Algeria

Brain tumors are irregular cell growths occurring in the brain or central spinal canal, classified as benign or malignant, posing challenges in diagnosis and treatment. Convolutional Neural Networks (CNNs) have become powerful tools in medical imaging analysis, particularly for classifying and segmenting brain tumors from Computed Tomography (CT) scans or Magnetic Resonance Imaging (MRI). However, using a single pretrained CNN model may not fully capture the data's variability and complexity, potentially reducing classification accuracy due to missed features. In this paper, we propose an ensemble fusion method integrating three deep CNNs: VGG19, GoogLeNet, and ResNet50 to classify brain MR images into Glioma tumor, Meningioma tumor, Pituitary tumor, and Normal brain categories. By combining these models into an ensemble, we aim to incorporate all pertinent data features, enhancing classification accuracy and generalization to new data. We employed the Particle Swarm Optimization (PSO) algorithm to optimize the penalty parameter C for linear SVM and select optimal features from multiple CNNs, enabling our ensemble model to significantly enhance performance with a reduced feature subset. Our ensemble approach achieved outstanding results across all metrics: accuracy, precision, sensitivity, and F1-score was achieved 99.30%, accompanied by a high specificity of 99.70%. Moreover, our framework demonstrates competitive performance compared to prior studies. ©2025 The authors.

关键词： Particle swarm optimization (PSO)

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Lightweight design and deployment of object detection model for low-light scenes 4

Lightweight design and deployment of object detection model ...

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4th International Conference on Computer Vision, Application, and Algorithm, CVAA 2024

作者： Sun, Kangjian Huo, Ju Jiang, Xiaona Gao, Yichao Cai, Chen School of Electrical Engineering and Automation Harbin Institute of Technology Harbin China National Key Laboratory of Modeling and Simulation for Complex Systems Harbin China China FAW Corporation Limited Changchun China College of Design and Engineering National University of Singapore Singapore Signal and Communication Research Institute China Academy of Railway Sciences Beijing China

ISBN: (数字)9781510687622

ISBN: (纸本)9781510687615

Low-light scenes are common in fields such as autonomous driving, which tests the robustness of intelligent systems. This paper tests the performance of object detection in low-light scenes based on the YOLOv8n model. In order to solve the constraint of limited computing power of embedded devices, the YOLOv8n model is adjusted through model pruning and knowledge distillation. The complexity of the model is reduced through these lightweight operations. While ensuring the detection performance as much as possible, the multiply-accumulate operations (MACs) and parameters of the model decreased by about 40% and 27% respectively. The proposed model is evaluated on the Exclusively Dark (ExDARK) dataset and achieves a mean average precision (mAP) value of 0.672. In addition, the proposed model is migrated to the embedded platform NVIDIA Jetson Xavier NX. The deployment process is optimized by multi-process scheduling and multi-thread scheduling. Experiments are also conducted on real data, and the results show that the proposed model can provide a feasible solution for vision-based nighttime autonomous driving. © 2025 SPIE.

关键词： Object detection Deep learning Image processing

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