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29th IEEE International Conference on Parallel and Distributed Systems, ICPADS 2023

作者： Zeng, Yan Huang, Chengchuang Ni, Yijie Zhou, Chunbao Zhang, Jilin Wang, Jue Zhou, Mingyao Xue, Meiting Zhang, Yunquan Hangzhou Dianzi University School of Computer Science and Technology Hangzhou310018 China Ministry of Education Key Laboratory for Modeling and Simulation of Complex Systems Hangzhou310018 China Data Security Governance Zhejiang Engineering Research Center Hangzhou310018 China Hangzhou Dianzi University School of ITMO Joint Institute Hangzhou310018 China Institute of Computer Network Information Center of the Chinese Academy of Sciences Beijing100086 China HuaWei China Institute of Computing Technology of the Chinese Academy of Sciences State Key Laboratory of Computer Architecture Beijing100086 China

ISBN: (纸本)9798350330717

As the size of datasets and neural network models increases, automatic parallelization methods for models have become a research hotspot in recent years. The existing auto-parallel methods based on machine learning or graph algorithms still have issues with search efficiency and applicability. This paper proposes an automatic parallel method based on a dual-population genetic algorithm, TGA, which transforms model partitioning and placement into an integer linear programming problem and constructs a cost model to evaluate the solution. The solution space is built using the neural network's dataflow graph and device cluster's topology, and the dual-population genetic algorithm is used to search for the optimal model parallel strategy. Experiments with various models show that the proposed method can improve single-step execution time by up to 42% compared to the Baechi method and up to 37.7% compared to the Hierarchical method. © 2023 IEEE.

关键词： Auto-Parallel Distributed machine learning Genetic algorithm Integer linear programming Model parallelism

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Well-posedness analysis of the Cahn-Hilliard-Biot model

arXiv

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arXiv 2023年

作者： Riethmüller, Cedric Storvik, Erlend Both, Jakub Wiktor Radu, Florin Adrian Institute of Applied Analysis and Numerical Simulation University of Stuttgart Germany Department of Computer Science Electrical Engineering and Mathematical Sciences Western Norway University of Applied Sciences Norway Center for Modeling of Coupled Subsurface Dynamics Department of Mathematics University of Bergen Norway

We investigate the well-posedness of the recently proposed Cahn-Hilliard-Biot model. The model is a three-way coupled PDE of elliptic-parabolic nature, with several nonlinearities and the fourth order term known to the Cahn-Hilliard system. We show existence of weak solutions to the variational form of the equations and uniqueness under certain conditions of the material parameters and secondary consolidation, adding regularizing effects. Existence is shown by discretizing in space and applying ODE-theory (the Peano-Cauchy theorem) to prove existence of the discrete system, followed by compactness arguments to retain solutions of the continuous system. In addition, the continuous dependence of solutions on the data is established, in particular implying uniqueness. Both results build strongly on the inherent gradient flow structure of the model. Copyright © 2023, The Authors. All rights reserved.

关键词： Variational techniques

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Dynamic Neural Potential Field: Online Trajectory Optimization in Presence of Moving Obstacles

arXiv

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arXiv 2024年

作者： Staroverov, Aleksey Alhaddad, Muhammad Narendra, Aditya Mironov, Konstantin Panov, Aleksandr The Artificial Intelligence Research Institute Moscow105064 Russia Federal Research Center "Computer Science and Control Moscow117312 Russia Center of Cognitive Modeling Moscow Institute of Physics and Technology Dolgoprudny141701 Russia Faculty of Electrical and Electronic Engineering University of Aleppo Syria Ufa University of Science and Technology Ufa450000 Russia

We address a task of local trajectory planning for the mobile robot in the presence of static and dynamic obstacles. Local trajectory is obtained as a numerical solution of the Model Predictive Control (MPC) problem. Collision avoidance may be provided by adding repulsive potential of the obstacles to the cost function of MPC. We develop an approach, where repulsive potential is estimated by the neural model. We propose and explore three possible strategies of handling dynamic obstacles. First, environment with dynamic obstacles is considered as a sequence of static environments. Second, the neural model predict a sequence of repulsive potential at once. Third, the neural model predict future repulsive potential step by step in autoregressive mode. We implement these strategies and compare it with CIAO* and MPPI using BenchMR framework. First two strategies showed higher performance than CIAO* and MPPI while preserving safety constraints. The third strategy was a bit slower, however it still satisfy time limits. We deploy our approach on Husky UGV mobile platform, which move through the office corridors under proposed MPC local trajectory planner. The code and trained models are available at https://***/CognitiveAISystems/ Dynamic-Neural-Potential-Field. © 2024, CC BY.

关键词： Cost functions

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Chances and Challenges of ChatGPT and Similar Models for Education in M&S

Chances and Challenges of ChatGPT and Similar Models for Edu...

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2023 Winter simulation Conference, WSC 2023

作者： Tolk, Andreas Barry, Philip Loper, Margaret L. Rabadi, Ghaith Scherer, William T. Yilmaz, Levent The Mitre Corporation Modeling and Analysis Innovation Center 1001 Research Park Blvd #200 CharlottesvilleVA22911 United States L3Harris Corporation Mission Analysis Group 2235 Monroe Street HerndonVA20171 United States Georgia Tech Research Institute Georgia Institute of Technology AtlantaGA30308 United States University of Central Florida School of Modeling Simulation and Training 3100 Technology Pkwy OrlandoFL32826 United States University of Virgina Department of Systems and Information Engineering CharlottesvilleVA22904 United States Auburn University Samuel Ginn College of Engineering Computer Science and Software Engineering AuburnAL36849 United States

ISBN: (纸本)9798350369663

This position paper summarizes the inputs of a group of experts from academia and industry presenting their view on chances and challenges of using ChatGPT within modeling and simulation education. The experts also address the need to evaluate continuous education as well as education of faculty members to address scholastic challenges and opportunities while meeting the expectation of industry. Generally, the use of ChatGPT is encouraged, but it needs to be embedded into an updated curriculum with more emphasis on validity constraints, systems thinking, and ethics. © 2023 IEEE.

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Numerical investigation of magnetized nanofluid flow in a non-Darcian medium with convective heating conditions across a rotating disk

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International Journal of Numerical Methods for Heat and Fluid Flow 2025年第5期35卷 1736-1763页

作者： Bhatti, Muhammad Mubashir Ellahi, R. Sait, Sadiq M. Department of Material Science Innovation and Modelling North-West University Mmabatho South Africa Department of Physics College of Science Korea University Seongbuk-gu South Korea Department of Mathematics and Statistics International Islamic University Islamabad Pakistan Center for Modeling and Computer Simulation Research Institute King Fahd University of Petroleum and Minerals Dhahran Saudi Arabia Department of Mechanical Engineering University of California Riverside CA United States Department of Computer Engineering King Fahd University of Petroleum and Minerals Dhahran Saudi Arabia Interdisciplinary Research Center for Smart Mobility and Logistics King Fahd University of Petroleum and Minerals Dhahran Saudi Arabia

Purpose: A novel approach of Buongiorno and Arrhenius energy models is proposed to examine magnetized nanofluid flow saturated in a non-Darcian medium with convective boundary conditions over a rotating disk. The proposed work has substantial applications in the domain of Heat Transfer within industrial operations, including power plants, electronic devices and nuclear reactors. It also pertains to the design of energy-efficient systems, rotating machinery and equipment such as centrifugal pumps, turbines and rotating heat exchangers. It is also pertinent to environmental engineering, which deals with fluid filtration and thermal management, and biomedical engineering, which includes drug delivery systems and the treatment of hyperthermia. It also discusses applications of magnetic fields, such as magnetorheological fluids, magnetic refrigeration and magnetic cooling systems. Design/methodology/approach: The Von Karman’s methodology is used to develop a mathematical formulation. The resulting series of nonlinear differential equations are solved by generalized differential quadrature (GDQ) technique. The Newton–Raphson iterative method is used to get numerical solutions. Findings: Effects of evolving parameters such as radial velocity, azimuthal velocity, transverse velocity, thermal and concentration patterns are examined through graphs and tables. The outcomes of skin friction coefficient, Nusselt number, Sherwood number and residual error are also presented. A comparison with the existing literature has been made as a special case for the validation of results. Originality/value: A blend framework of Buongiorno and Arrhenius energy models for magnetized nanofluid flow across a uniformly rotating disk inside a non-Darcian structure with convective boundary conditions is presented. © 2025, Emerald Publishing Limited.

关键词： Arrhenius energy Buongiorno model Convective boundary conditions Generalized differential quadrature approach Magnetized nanofluid flow Non-Darcy medium

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Integrated Sensing, Localization, and Communication in Holographic MIMO-enabled Wireless Network: A Deep Learning Approach

TechRxiv

引用

TechRxiv 2023年

作者： Adhikary, Apurba Munir, Md. Shirajum Raha, Avi Deb Qiao, Yu Han, Zhu Hong, Choong Seon Department of Computer Science and Engineering School of Computing Kyung Hee University Yongin-si17104 Korea Republic of Virginia Modeling Analysis and Simulation Center Department of Electrical and Computer Engineering Old Dominion University SuffolkVA23435 United States Department of Computer Science and Engineering Kyung Hee University Yongin-si17104 Korea Republic of Department of Artificial Intelligence School of Computing Kyung Hee University Yongin-si17104 Korea Republic of Electrical and Computer Engineering Department University of Houston HoustonTX77004 United States

The impending sixth-generation wireless communication networks are anticipated to guarantee mass connectivity, high integration, and lower power consumption for generating the required beamforming. To achieve these goals, an artificial intelligence (AI) framework is proposed by utilizing holographic MIMO-assisted integrated sensing, localization, and communication. The proposed AI framework ensures lower power consumption to activate the minimum number of grids from the holographic grid array for the generation of holographic beamforming. An optimization problem is formulated to maximize the signal-to-interference-plus-noise ratio received by the users, which in turn maximizes the utility function for sensing considering the user distances, beampattern gains, sensing-communication loss, and dense locations controlling parameter. A novel AI-based framework is proposed to solve the formulated NP-hard optimization problem by decomposing it into two subproblems: the sensing problem and the communication resource allocation problem. First, a variational autoencoder (VAE) based mechanism is devised to solve the sensing problem mitigating the disputes to obtain the users’ exact location. Second, a sequential neural network-based scheme is utilized to allocate the communication resources to the heterogeneous users for generating the desired beamforming based on the findings of the VAE-based mechanism. Moreover, an extreme case power allocation strategy is presented once a large number of users enter the system. The extreme case power allocation strategy applies when the total power prediction exceeds the total system power for allocating the communication resources to the users. Finally, simulation results validate that the proposed AI-based framework outperforms the long short-term memory method with a cumulative power savings of 34.02% taking the ground truth power into account. Therefore, the proposed AI framework generates effective beamforming to serve the communicatio

关键词： Beamforming

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Adaptive fast-reaching nonsingular terminal sliding mode tracking control for quadrotor UAVs subject to model uncertainties and external disturbances

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Ain Shams engineering Journal 2023年第8期14卷

作者： Mobayen, Saleh El-Sousy, Fayez F.M. Alattas, Khalid A Mofid, Omid Fekih, Afef Rojsiraphisal, Thaned Graduate School of Intelligent Data Science National Yunlin University of Science and Technology 123 University Road Section 3 Douliou Yunlin640301 Taiwan Department of Electrical Engineering Prince Sattam Bin Abdulaziz University Al Kharj Saudi Arabia Department of Computer Science and Artificial Intelligence College of Computer Science and Engineering University of Jeddah Jeddah Saudi Arabia Department of Electrical and Computer Engineering University of Louisiana at Lafayette Lafayette United States Advanced Research Center for Computational Simulation Department of Mathematics Faculty of Science Chiang Mai University Chiang Mai50200 Thailand Data Science Research Center Department of Mathematics Faculty of Science Chiang Mai University Chiang Mai50200 Thailand

This paper proposes an adaptive fast-reaching nonsingular terminal sliding mode control approach for the position and attitude tracking control of a quadrotor UAV subject to model uncertainty and external disturbances. To this end, a fast-reaching nonsingular terminal sliding surface is defined with the aim of fast convergence of the tracking error. The fast reachability of the nonsingular terminal sliding surface is proven using the Lyapunov stability theory. Since, in practice, the upper bounds of model uncertainties and external disturbances are unknown, an adaptive control scheme is considered to approximate them. The fast-reaching nonsingular terminal sliding mode control approach was augmented with the adaptive scheme to ensure both, the fast convergence of the switching surfaces and the rejection of model uncertainties and external disturbances. The effectiveness of the proposed adaptive fast-reaching nonsingular terminal sliding mode control approach is assessed using simulations of a quadrotor system implemented in MATLAB/Simulink software. The obtained results are further compared to those of an existing approach in terms of tracking performance, robustness, and integrator of absolute-value of error criteria. © 2022 THE AUTHORS

关键词： Unmanned aerial vehicles (UAV)

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Composability Verification of Complex Systems Using Colored Petri Nets

Composability Verification of Complex Systems Using Colored ...

引用

simulation Winter Conference

作者： Imran Mahmood Syed Hassan Askari Hessam S. Sarjoughian Center for Research in Modeling & Simulation School of Electrical Engineering and Computer Science National University of Sciences and Technology Islamabad Pakistan Arizona Center for Integrative Modeling & Simulation School of Computing Information and Decision Systems Engineering Arizona State University Tempe Arizona USA

ISBN: (纸本)9781665433129

The discipline of component-based modeling and simulation offers promising gains including reductions in development cost, time, and system complexity. This paradigm promotes the use and reuse of modular components for adequate development of complex simulations. Achieving effective and meaningful model reuse through the composition of components still remains a daunting challenge. “Composability”, an integral part of this challenge, is the capability to select and assemble model components in various combinations to satisfy specific user requirements. In this paper, we propose the use of Colored Petri Nets for component-oriented model development, model composition, and the verification of composed models using state-space analysis technique. We present a case study of an elevator model as a proof of concept. Our case study explains the proposed process of developing and composing CPN-based model components and verifying the composed model using state-space analysis.

关键词： Analytical models Costs Petri nets Elevators Complexity theory Complex systems

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Chances and Challenges of Chatgpt and Similar Models for Education in M&S 23

Chances and Challenges of Chatgpt and Similar Models for Edu...

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Proceedings of the Winter simulation Conference

作者： Andreas Tolk Philip Barry Margaret L. Loper Ghaith Rabadi William T. Scherer Levent Yilmaz The MITRE Corporation Modeling and Analysis Innovation Center Charlottesville USA L3Harris Corporation Mission Analysis Group Herndon USA Georgia Tech Research Institute Georgia Institute of Technology Atlanta USA University of Central Florida School of Modeling Simulation and Training Orlando USA University of Virgina Department of Systems and Information Engineering Charlottesville USA Auburn University Samuel Ginn College of Engineering Computer Science and Software Engineering Auburn USA

ISBN: (纸本)9798350369663

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Perturbations and Phase Transitions in Swarm Optimization Algorithms

arXiv

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arXiv 2025年

作者： Vantuch, Tomáš Zelinka, Ivan Adamatzky, Andrew Marwan, Norbert Center ENET Technical University of Ostrava Czech Republic Modeling Evolutionary Algorithms Simulation and Artificial Intelligence Faculty of Electrical & Electronics Engineering Ton Duc Thang University Ho Chi Minh City Viet Nam Department of Computer Science Technical University of Ostrava Czech Republic Unconventional Computing Lab UWE Bristol United Kingdom Leibniz Association Potsdam Germany

Natural systems often exhibit chaotic behavior in their space-time evolution. Systems transiting between chaos and order manifest a potential to compute, as shown with cellular automata and artificial neural networks. We demonstrate that swarm optimization algorithms also exhibit transitions from chaos, analogous to a motion of gas molecules, when particles explore solution space disorderly, to order, when particles follow a leader, similar to molecules propagating along diffusion gradients in liquid solutions of reagents. We analyze these ‘phase-like’ transitions in swarm optimization algorithms using recurrence quantification analysis and Lempel-Ziv complexity estimation. We demonstrate that converging iterations of the optimization algorithms are statistically different from non-converging ones in a view of applied chaos, complexity and predictability estimating indicators. An identification of a key factor responsible for the intensity of their phase transition is the main contribution of this paper. We examined an optimization as a process with three variable factors – an algorithm, number generator and optimization function. More than 9.000 executions of the optimization algorithm revealed that the nature of an applied algorithm itself is the main source of the phase transitions. Some of the algorithms exhibit larger transition-shifting behavior while others perform rather transition-steady computing. These findings might be important for future extensions of these algorithms. © 2025, CC BY-NC-ND.

关键词： Cellular automata

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