Hierarchical Optimal Scheduling Of Integrated Energy System With Electric Vehicles Based On Empc,
2025
School of Control and Computer Engineering, North China Electric Power University, Beijing 102206, China; State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing 102206, China
Hierarchical Optimal Scheduling Of Integrated Energy System With Electric Vehicles Based On Empc, Miaomiao Ma, Zijuan Long, Zhiwei Ren, Yongqiang Cheng
Journal of System Simulation
Abstract: A hierarchical real-time optimization (HRTO) based on economic model predictive control is designed to address the issues of randomness and uncertainty of renewable energy and demand-side in integrated energy systems (IES) with electric vehicles. The optimization problem of the entire system is divided into three sub-problems: day-ahead rolling optimization, real-time rolling optimization, and tracking control. The day-ahead optimization strategy based on economic model predictive control is constructed to ensure that the operational units can meet users' demands. The optimal steady-state operating points of the entire IES are obtained through the real-time optimization layer. The tracking model predictive controller is …
Method For Dynamic Coalition Formation Of Wargame Agent For Force Cooperation,
2025
School of Electronic & Information Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, China
Method For Dynamic Coalition Formation Of Wargame Agent For Force Cooperation, Changhua Yao, Shanning Bi, Rufei Ma, Xiaohan Yu, Jiaqiang Li, Jinli Chen
Journal of System Simulation
Abstract: Regarding the issue of cooperative task alliance formation and adjustment in multi-agent dynamic confrontation scenarios at the tactical level, this method comprehensively considers factors such as target value, task allocation, and operator characteristics, as well as the benefits and costs of executing different types of tasks. we propose a targeted force coordination adjustment for dynamic task alliance formation based on behavioral constraints. The “MiaoSuan-Wise Winning Instant Strategy Human-Computer Confrontation Platform” of Chinese Academy of Sciences (CAS) is used as an experimental platform to conduct confrontation experiments. The experiment demonstrates that the proposed method improves the dynamic coordination ability of …
Research On Decision-Making Of Autonomous Driving In Highway Environment Based On Knowledge And Large Language Model,
2025
Department of computer science and technology, Dalian University of Technology, Liaoning 116081, China
Research On Decision-Making Of Autonomous Driving In Highway Environment Based On Knowledge And Large Language Model, Xiang Wang, Guozhen Tan
Journal of System Simulation
Abstract: Aiming at the lack of continuous learning and interpretability of current autonomous driving system, a decision model with cognition, generalization and learning ability is proposed. The model utilizes large language model (LLM) and attention mechanisms to understand and explain driving scenes. the system can accumulate and learn from driving experiences, continuously improving its decisionmaking ability. In a simulation environment, the closed-loop test decision model is applied in high-speed scenarios.The simulation results show that the success rate of the knowledge-driven model is 7% and 4% higher than those of the rule-based and data-driven methods. Additionally, the model exhibits generalization and …
Design And Realization Of Integrated Energy System Dynamic Stability Simulation And Steady-State Simulation System,
2025
China Electric Power Research Institute, Beijing 100192, China
Design And Realization Of Integrated Energy System Dynamic Stability Simulation And Steady-State Simulation System, Guixiong He, Xiaoqiang Jia, Shufeng Dong, Yonglu Han, Yonghua Chen, Yiming Zheng
Journal of System Simulation
Abstract: Aiming for“carbon peak”and“carbon neutrality”, the energy sector is undergoing significant reform. To address energy flow and planning optimization in integrated energy systems, a comprehensive simulation platform is developed. This platform combines physical and digital simulations with real-world validation and is modular in design, It includes an integrated energy model library, energy flow optimization, modeling management, real-time simulation, and energy monitoring. The platform enhances system safety, stability, and economic efficiency, While also improving planning and energy management. The paper analyzes the platform′s functional and physical architecture, introduces key modules, establishes dynamic and steady-state model libraries, and optimizes energy flow using …
Survey On Large Language Agent Technologies For Intelligent Game Theoretic Decision-Making,
2025
College of Intelligence Science and Technology, National University of Defense Technology, Changsha 410073, China
Survey On Large Language Agent Technologies For Intelligent Game Theoretic Decision-Making, Xueqiang Gu, Junren Luo, Yanzhong Zhou, Wanpeng Zhang
Journal of System Simulation
Abstract: The development of artificial intelligence technology has greatly promoted the transformation of the solving paradigm of intelligent game decision problems. From optimal solution, equilibrium solution to adaptive variable solution, how to build an intelligent game adaptive decision agent based on generative large model is full of challenges. The force distribution and multi-entity coordination in the game strong confrontation environment are the core issues in the study of troop deployment and operational coordination. Based on the methods of strategy reinforcement learning, strategy game tree search and strategy preference voting based on skill, ranking and preference meta-game model construction, a large …
Improved Hybrid Optimization Algorithm For Multi-Objective Ipps Problem,
2025
School of Mechanical and Electrical Engineering, Hohai University, Changzhou 213200, China
Improved Hybrid Optimization Algorithm For Multi-Objective Ipps Problem, Wenbin Gu, Jiexia Qing, Jie Fang, Siqi Liu
Journal of System Simulation
Abstract: For the problem of multi-objective integrated process planning and scheduling (MOIPPS), an improved hybrid optimization algorithm considering global and local optimum is proposed to optimize two objectives about minimum makespan and energy consumption. A multi-objective problem model and solution framework are established by analyzing the difference and connection between process planning and scheduling in integrated system. A hybrid optimization algorithm is proposed for the two-stage integration problem. In the process planning stage, global search algorithm is employed to provide a variety of process schemes for the integrated system and to ensure the global search performance of the integrated algorithm. …
Research On Modeling, Optimization And Application Of Aeroengine Oil System,
2025
Nanjing University of Aeronautics and Astronautics Civil aviation college, Nanjing 211106, China
Research On Modeling, Optimization And Application Of Aeroengine Oil System, Shijie Huang, Zhensheng Zhang, Jing Cai, Rui Zhang
Journal of System Simulation
Abstract: In response to the high cost and long cycle of using experimental methods for monitoring, diagnosing, and predicting lubricating oil system, a simulation model for oil system is constructed and optimized, and the application of the model in health management of oil system is proposed. Based on the physical characteristics of the components in the oil system, subsystem models for ventilation, oil supply, thermodynamics, and oil return are constructed using a certain engine oil system as an example, and the whole oil system model is constructed and solved iteratively. The model is optimized by combining particle swarm optimization and …
Robot Path Planning Based On Ant Colony Algorithm With Dual Heuristic Information,
2025
Institute of Automation, Qilu University of Technology (Shandong Academy of Sciences), Jinan 250014, China
Robot Path Planning Based On Ant Colony Algorithm With Dual Heuristic Information, Xiaohui Zhou, Yanqiang Li, Yong Wang, Decai Zhao, Xiaoyao Yang
Journal of System Simulation
Abstract: The traditional ant colony algorithm is characterized by a slow convergence speed, numerous turning points, and a tendency to fall into local minima. These characteristics make the algorithm less effective for path planning research in mobile robotics. Therefore, this paper proposes an improved ant colony algorithm and applies it to global path planning for robots. The A* algorithm is used to quickly plan a path and increase the initial pheromone of that path, so that the improved algorithm is guided by the global path during the local search, preventing excessive ants from entering dead ends, and reducing the randomness …
Research On Modeling Methods For Industrial Core Capability Architecture Based On The Dodaf Framework,
2025
Defense Industry Program Evaluation Center of sastind, Beijing 100039, China
Research On Modeling Methods For Industrial Core Capability Architecture Based On The Dodaf Framework, Xiaoqiang Dou, Yan Liu, Zhilong Zhao, Chao Fu, Fulin Zhang, Shanshan Zou
Journal of System Simulation
Abstract: Against the backdrop of the industrial sector actively pursuing digital capability building, this paper describes the necessity and current status of architecture theory methods guiding industrial core capability construction. It proposes the conceptual connotation of industrial core capability architecture and four key modeling elements. Based on DoDAF, it conducts the overall design of industrial core capability architecture. By integrating systems engineering principles, it establishes a five-stage process model for capability-building activities, embedding critical elements such as capability/business/ application/data/technology architecture viewpoint, and explains data model design, and logical compositions of various viewpoints. By selecting a capability building project in a …
A Simulating Framework Construction Method About New Distributed Confrontation,
2025
PLA 63893 Troops, Luoyang 471000, China
A Simulating Framework Construction Method About New Distributed Confrontation, Zhipeng Liu, Yanyang Gu, Baojie Hu, Fangjun He, Zhipeng Fan
Journal of System Simulation
Abstract: The new distributed confrontation in future emphasizes systematic combat and flexible use of power in the resistance environment. To study and analyze the potential threats of such new forms of distributed confrontation, this paper proposes a system confrontation strategy focused on decisionmaking confrontation from the perspective of network and electromagnetic space. In addition, a highly flexible and saleable behavior model adversarial framework is proposed. By parameterizing the network and electrical countermeasure strategy, an adversarial model based on typical airspace scenarios is designed, and the confrontation effectiveness of traditional multifunctional platforms and distributed units is quantitatively compared and analyzed. The …
Radar Precursors To Severe Weather Reports In Left-Moving Supercells,
2025
University of Nebraska-Lincoln
Radar Precursors To Severe Weather Reports In Left-Moving Supercells, Eric A. Carothers
Department of Earth and Atmospheric Sciences: Dissertations, Theses, and Student Research
While much research has examined dual-polarimetric signatures of right-moving supercells, very little has been done with left-moving supercells. Given that left-moving supercells are thought to be disproportionate producers of large hail, understanding their internal dynamics is vitally important. This study examines differences and trends in the dual-polarimetric signatures of left-moving supercells to identify precursors to severe weather reports. A dataset of left-moving supercells associated with severe weather reports was created. These storms are processed with an automated analysis algorithm that identifies and quantifies the polarimetric signatures in each storm. A method for analysis of differences and trends in their dual-polarization …
Learning Behaviors In Physics-Informed Deep Learning,
2025
East Tennessee State University
Learning Behaviors In Physics-Informed Deep Learning, Alex Glover
Electronic Theses and Dissertations
Physics-informed deep learning is a methodology in artificial intelligence aimed at combating the large training data requirement and the barrier of domain awareness that deep learning architectures commonly face in applications. Stochastic modeling integrated into the predictive models provides that domain knowledge. Variations of the Intelligent Driving Model impact the learning behaviors of the joint-training architecture. This thesis examines the effect of substituting the standard linear Intelligent Driving Model with a modified nonlinear version, as applied to real human driving behavior on the I-80 interstate. The experimentation also critically evaluates the complications that impede the viability of this architecture in …
Using Gaussian Process Regression To Learn Thermodynamic Equations Of State With Uncertainty Quantification,
2025
University of Arkansas, Fayetteville
Using Gaussian Process Regression To Learn Thermodynamic Equations Of State With Uncertainty Quantification, Austen T. Lee
Chemical Engineering Undergraduate Honors Theses
This study investigates the use of derivative-informed Gaussian Process (GP) models to estimate thermodynamic behavior across temperature and density by building a Helmholtz-based equation of state. Argon, a stable monatomic gas, was chosen as a case study within the vapor region. The GP model was trained using values of experimentally measurable properties found by taking first and second derivatives of the original potential function. Results show that while the GP model offered uncertainty quantification and informed thermodynamic behavior, it predicted values that deviated from the ground truth depending on the property. The model exhibited high confidence in regions with substantial …
Advancing Precision And Autonomy In Agriculture And Medical Imaging Through Ai And Computer Visions,
2025
Florida Institute of Technology
Advancing Precision And Autonomy In Agriculture And Medical Imaging Through Ai And Computer Visions, Tan-Hanh Pham
Theses and Dissertations
Deep learning has revolutionized numerous fields by enhancing precision, automation, and decision-making capabilities. This dissertation explores its applications in agriculture and medical image processing, introducing novel methodologies to improve accuracy and efficiency in these domains. These fields hold critical societal importance -- agriculture underpins global food security and sustainability, while medical imaging drives advancements in diagnostics and personalized healthcare, both benefiting significantly from data-driven innovations. In agriculture, deep learning is applied to precision spray systems through droplet analysis. Specifically, a generative model is designed to create synthetic droplet images, addressing the challenge of limited training samples, which are expensive …
Towards Advancing Streamflow And Peak Flow Prediction With Machine Learning: Identifying Infrastructure At Risk,
2025
University of Nebraska-Lincoln
Towards Advancing Streamflow And Peak Flow Prediction With Machine Learning: Identifying Infrastructure At Risk, Sudan Pokharel
Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–
Due to climate change and its impact, the need for adaptive strategies for natural disaster mitigation and resource management has never been more urgent. Central to this is water resource management, which is essential for sustainable human activities, ecological balance, and the mitigation of natural hazards like floods. Streamflow is a crucial element of water resource management and plays a vital role in planning and building water infrastructure, implementing emergency response plans, supporting flood mitigation initiatives, and regulating agricultural and industrial use. However, accurate prediction of streamflow still remains a challenge due to the complex non-linear and non-stationary interaction between …
Physics Embedded Neural Network: A Novel Data-Free Numerical Method For Solving Computational Physics Problems,
2025
University of Nebraska-Lincoln
Physics Embedded Neural Network: A Novel Data-Free Numerical Method For Solving Computational Physics Problems, Pawan Gaire
Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–
A novel approach for solving partial differential equations (PDEs) using neural networks for scientific computing is introduced. The proposed approach, referred to as physics-embedded neural network (PENN), features a unique architecture that incorporates the PDE and boundary conditions information directly within the final fully-connected layer of the feed-forward neural network (NN). The key aspect of PENN is the parallel numerical embedding of a differential equation associated with physical problems within the activation function of the network’s final layer. This integration leads to a new class of computational solvers competitive with classical methods like the Finite Element Method (FEM) and capable …
Guest Editorial: When Multimedia Meets Food: Multimedia Computing For Food Data Analysis And Applications,
2025
Singapore Management University
Guest Editorial: When Multimedia Meets Food: Multimedia Computing For Food Data Analysis And Applications, Weiqing Min, Shuqiang Jiang, Petia Radeva, Vladimir Pavlovic, Chong-Wah Ngo, Kiyoharu Aizawa, Wanqing Li
Research Collection School Of Computing and Information Systems
Food is central in our life for its fundamental role in our survival, health, mood and culture. The deployment of various networks (e.g., IoT and mobile networks), devices (e.g., hyperspectral imaging devices, electronic nose/tongue), databases (e.g., nutrition tables and food compositional databases), recipe-sharing websites (e.g., Yummly and Meishijie) and social media (e.g., Twitter and Weibo) has generated unprecedented volumes of multi-modal food data. Such multi-source multi-modal food data provides new perspectives to analyze and understand food consumption via multimedia computing. Riding on the wave of AI, food-oriented multimedia computing integrates AI, multimedia technology and food science to enable a wide …
Creating Talking Points For Client Advisers At Banks To Promote Sustainable Investing,
2025
Gojek Singapore
Creating Talking Points For Client Advisers At Banks To Promote Sustainable Investing, Wewe Zi Yi, Pradeep Varakantham, Alan Megargel
Research Collection School Of Computing and Information Systems
Environmental, social and governance (ESG) factors have become key nonfinancial factors for investors to evaluate companies with respect to understanding material risks and growth opportunities. While not mandatory, companies are providing ESG reports that outline progress in different ESG metrics (six broad metrics and 15 specific ones). Client advisers (CAs) read these reports to identify key metrics of interest to investors. Given the number of companies and investment products, however, it is not feasible for CAs to read all the reports, which can sometimes run into tens or hundreds of pages). The authors have developed multiple frameworks building on leading …
Predicting The Unpredictable: Predicting The March Madness Champion Using Statistical Modeling,
2025
Bryant University
Predicting The Unpredictable: Predicting The March Madness Champion Using Statistical Modeling, Jack Sweeney
Honors Projects in Information Systems and Analytics
One of the more exciting and hardest parts of the men's college basketball postseason tournament, named March Madness, is to pick who wins each game and determine the overall champion of the tournament. The data analysis conducted will help determine the overall tournament winner. A machine learning model is implemented using college basketball metrics from previous years to determine the overall winner of this prestigious tournament in 2025. The model was able to pick up the winner in 2024. The result also finds that the most important features in determining the winner of the tournament are shooting guard height, small …
Survey On Intelligent Planning Methods From Large Language Models Perspective,
2025
College of Intelligence Science and Technology, National University of Defense Technology, Changsha 410073, China
Survey On Intelligent Planning Methods From Large Language Models Perspective, Yanzhong Zhou, Junren Luo, Xueqiang Gu, Wanpeng Zhang
Journal of System Simulation
Abstract: Starting from the perspective of large language models, this paper gives an overview of the definition and development of intelligent planning, and briefly introduces the traditional methods of intelligent planning; based on the close relationship between large language model intelligent agents and intelligent planning, introduces the architecture of large language models and typical large model intelligent agents; focusing on the intelligent planning for large language models, combs through the learning of planning languages, chain of thought, feedback optimization, and process automation; combining with the current challenges and difficulties, introduces the outlook of cutting-edge research on intelligent planning with large …
