Four-Dimensional Gradient Integration: Reform And Practice On Modeling And Simulation Courses For Management Disciplines,
2026
School of Economics & Management, Nanjing Tech University, Nanjing 211816, China
Four-Dimensional Gradient Integration: Reform And Practice On Modeling And Simulation Courses For Management Disciplines, Bin Wu, Huagang Tong, Zhiyong Cui, Feiyi Yan
Journal of System Simulation
In the process of course implementation, local universities generally face problems such as students' weak mathematical and physical foundations, disconnection between teaching content and technological frontiers, single teaching method, and fragmented cultivation of practical capability. Based on long-term teaching reform practice, a four-dimensional gradient integration teaching model of "value guidance, knowledge restructuring, scenario innovation, and capability progression" was proposed, and its theoretical logic, implementation path, and practical effect were systematically elaborated. This model can effectively stimulate students' intrinsic motivation for learning, promote the digital and intelligent updating of teaching content, expand the teaching scenario of industry-education integration, and realize …
Improved Nsga-Ii For Dual-Resource Flexible Job Shop Scheduling Considering Worker Load,
2026
School of Management Engineering, Zhengzhou University of Aeronautics, Zhengzhou 450046, China
Improved Nsga-Ii For Dual-Resource Flexible Job Shop Scheduling Considering Worker Load, Guohui Zhang, Yuan Ren, Changjun Wu, Xiaofei Kou
Journal of System Simulation
For the dual-resource-constrained flexible job shop scheduling problem considering worker load, an evolutionary algorithm integrating reinforcement learning was proposed. A three-stage encoding conforming to the problem characteristics was designed, and three initialization methods were combined to improve the population quality; a left-insertion decoding method based on worker load was designed to ensure that the completion time of the operation is less than the maximum processable time of the worker on the current day; two neighborhood structures based on the critical path were constructed to enhance the local exploration ability of the population; reinforcement learning was integrated to enable the …
Parameter Identification Of Permanent Magnet Synchronous Motors Based On Igwo-Aekf,
2026
School of Mechanical Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China
Parameter Identification Of Permanent Magnet Synchronous Motors Based On Igwo-Aekf, Lei Yao, Zijian Zheng, Tianhao Li, Yulun Chi
Journal of System Simulation
The accuracy of the traditional EKF in parameter identification of the PMSM tends to be degraded under load changes or abrupt changes in internal parameters of the motor. This paper proposes an IGWO adaptive interconnected Kalman filter observer, which constructs an adaptive mechanism that combines the innovation and residuals to achieve dynamic adjustment of the process noise matrix and system noise matrix, thereby avoiding the problem of reduced parameter identification accuracy due to reliance on fixed covariance matrices under operating condition changes. A multi-parameter interconnected coupling compensation identification model for PMSM is built to mitigate the effects of measurement noise …
Research On Control Strategy For Shortest Time Occupancy Of Auv Based On Improved Td3,
2026
School of Mechanical Engineering, Southwest Jiaotong University, Chengdu 610031, China
Research On Control Strategy For Shortest Time Occupancy Of Auv Based On Improved Td3, Wenzhe Ren, Min Li, Xiangguang Zeng, Tao Zhang, Dijie Xie, Bei Peng
Journal of System Simulation
Existing occupancy models fail to fully consider the interference of underwater time-varying ocean currents and task time constraints, and AUVs lacks real-time motion control. To address these issues, a shortest time occupancy method based on quantile regression and distributed TD3 was proposed. The Bayesian inference method was used to identify hydrodynamic parameters, and the kinematic and dynamic models of AUVs were established; the shortest time occupancy equation was constructed, and the occupancy target point and occupancy time were solved; a first-order Gauss-Markov process was introduced to simulate the time-varying ocean current environment, and the training of control strategy for AUV …
Impact Angle-Constrained Dive Maneuver Guidance Method For Hypersonic Vehicles,
2026
School of Missile Engineering, Rocket Force University of Engineering, Xi'an 710025, China
Impact Angle-Constrained Dive Maneuver Guidance Method For Hypersonic Vehicles, He Wang, Gang Lei, Shaopeng Li
Journal of System Simulation
To address the impact angle control and maneuvering flight problem of hypersonic vehicles in the dive phase, this paper proposed a tracking guidance method integrating optimal Bézier curves and super-twisting sliding mode control. A three-dimensional Bézier curve trajectory satisfying the impact angle constraint was designed, and the maneuvering flight in dive phase was achieved by adding dynamic control points; to optimize impact velocity, a rapid calculation method for the impact velocity of the vehicle flying along the curve was derived, and the optimal reference trajectory was obtained by optimizing the control point parameters through sequential quadratic programming; to ensure …
Two-Stage Calibration And Optimization Method For Microscopic Traffic Simulation Model Parameters Based On Neural Network Surrogate Models,
2026
School of Civil Engineering and Transportation, Guangzhou University, Guangzhou 510700, China
Two-Stage Calibration And Optimization Method For Microscopic Traffic Simulation Model Parameters Based On Neural Network Surrogate Models, Yijia Liu, Chenjing Zhou, Dong Pan, Jian Rong, Yang Xiao
Journal of System Simulation
A two-stage calibration and optimization method is proposed to address the problem that parameter calibration methods for microscopic traffic simulation models are time-consuming. In the first stage, a surrogate model based on neural networks is trained to establish the mapping relationship between model parameters and evaluation indicators, and a genetic algorithm (GA) is combined to screen candidate parameters. In the second stage, after obtaining the approximate optimal parameters, by employing this set of parameters as initial values, a genetic algorithm is re-executed by combining the real simulation model for optimization to further improve calibration accuracy. Experimental results show that the …
Application Of Improved Multi-Objective Differential Algorithm In Robotic Arm Multi-Objective Trajectory Planning,
2026
School of Automation and Electrical Engineering, Lanzhou University of Technology, Lanzhou 730000, China
Application Of Improved Multi-Objective Differential Algorithm In Robotic Arm Multi-Objective Trajectory Planning, Manqiang Liu, Ziqiang Shang
Journal of System Simulation
It is difficult for single-objective trajectory planning methods to meet the requirements of precision, diversity and complexity of robotic arms. A trajectory planning model based on an improved multi-objective differential evolution algorithm (guided multi-objective differential evolution, GMODE) algorithm is proposed. Cubic polynomial interpolation and B-spline curves are employed to construct multi-objective functions, while GMODE is adopted to overcome the limitations of traditional algorithms, such as insufficient population diversity, the tendency to fall into local optima, and slow convergence. A grouping strategy, parameter generation mechanism, and elite mutation based on fuzzy Cmeans clustering are introduced to optimize B-spline control nodes. …
Current Status And Prospects Of Complex Scene Reconstruction Based On Gaussian Splatting,
2026
College of Artificial Intelligence & Computer Science, Xi'an University of Science and Technology, Xi'an 710054, China; State Key Laboratory of Virtual Reality Technology and Systems, Beihang University, Beijing 100191, China
Current Status And Prospects Of Complex Scene Reconstruction Based On Gaussian Splatting, Hong'an Li, Jiale Yang, Qingfang Liu, Yu Shi
Journal of System Simulation
Three-dimensional Gaussian splatting (3DGS) provides an alternative approach for novel view synthesis from the perspective of explicit representation. By reconstructing scenes using 3D Gaussian primitives and replacing traditional ray integration with a point-based rasterization process, it not only improves training and rendering efficiency but also offers new insights for complex scene reconstruction. This paper divided 3DGS-based complex scene reconstruction methods into three major categories and elaborated on them around large-scale scenes, sparse views, and dynamic scenes. It reviewed the current development status of this field and pointed out possible future research directions.
Experimental And Simulation Study On Energy Release Of Extended Sources Influenced By Atmospheric Pressure Variation,
2026
Unmanned System Research Institute, Northwestern Polytechnical University, Xi'an 710000, China; Academy of Opto-Electronic, China Electronic Technology Group Corporation (AOE CETC), Tianjin 300308, China
Experimental And Simulation Study On Energy Release Of Extended Sources Influenced By Atmospheric Pressure Variation, Kai Guo, Feiyu Zhao, Hao Zhang, Liang Wang, Kai Zhang
Journal of System Simulation
To investigate the energy release characteristics of extended sources in low-pressure environments, a combined experiment and simulation approach was adopted. Four typical altitudecorresponding pressures were selected as experimental conditions. An infrared thermal imager was employed to monitor parameters such as combustion temperature, radiance, and combustion area during the combustion process of the extended source. When the pressure decreases from 101 kPa to 30 kPa, the ignition time of the extended source doubles; the total energy release attenuates by 44.78%, and the combustion area reduces by 45.95%, but the fluctuations of peak temperature and average temperature are less than 3%, …
Research On Output Feedback Control Based On Reinforcement Learning For Overhead Crane,
2026
School of Technology, Beijing Forestry University, Beijing 100083, China
Research On Output Feedback Control Based On Reinforcement Learning For Overhead Crane, Minghui Li, Daoxiang Gao
Journal of System Simulation
An output feedback control algorithm is designed based on reinforcement learning for the optimal control problem of overhead crane system. A high gain observer (HGO) is designed using output data to estimate the unmeasurable states of the overhead crane system. Based on the estimated states from the high-gain observer, a policy iteration (PI) method is designed with integral reinforcement learning, which uses Critic and Actor neural networks to approximate the optimal value function and control strategy, and adjusts the neural network weights in real time through online adaptive algorithms. According to the Lyapunov stability theory, the uniform ultimate boundedness of …
Object Detection Networks And Their Interpretability In Rain, Fog, And Snow Scenarios,
2026
Liaoning Technical University, Huludao 125105, China
Object Detection Networks And Their Interpretability In Rain, Fog, And Snow Scenarios, Yanji Jiang, Jiayu Cui, Hao Dong, Daqian Liu, Bowen Fei, Miao Yu, Jinshan Huang
Journal of System Simulation
To address the severe degradation of object detection performance under extreme weather conditions, a detection framework based on the Kolmogorov-Arnold theorem, termed KADet, is proposed. A dynamic Kolmogorov-Arnold Transformer is designed, which leverages learnable nonlinear activation functions to enhance the modeling capability for complex distortions introduced by weather degradation. A Kolmogorov-Arnold spatial-channel network is developed by integrating KAT convolution with spatial-channel convolution to strengthen feature learning of relationships between targets and backgrounds in degraded scenes. An improved loss function is introduced to guide the optimization of the activation functions, and interpretability is analyzed through visualization of their curves. …
Pattern Identification And Mechanism Analysis Of Nonlinear Oscillations In Grid-Connected Direct-Drive Wind Turbines,
2026
Electric Power Research Institute, Guangxi Power Grid Co. , Ltd. , Nanning 530023, China; Guangxi Key Laboratory of Intelligent Control and Maintenance of Power Equipment, Nanning 530023, China
Pattern Identification And Mechanism Analysis Of Nonlinear Oscillations In Grid-Connected Direct-Drive Wind Turbines, Libin Wen, Shaopu Tang, Xianfa Hu, Jinji Xi, Tongtong Zhang, Hong Hu, Weijie Zhang
Journal of System Simulation
Taking a grid-connected direct-drive wind turbine system as an example, a comprehensive model is developed that incorporates nonlinear elements such as prime mover control, machine-side and grid-side converter control, multiple limiters, and control switching. A nonlinear oscillation pattern identification method based on density clustering and manual identification is proposed. The results show that the proposed method can efficiently identify various typical patterns, including quasi-constant amplitude oscillations, period-doubling oscillations, and chaotic oscillations. Oscillations dominated by nonlinear factors such as control switching, limiter collision, and limiter saturation are essentially caused by the transition of the associated components from passive responses to …
Iterative Evolution And Innovation Of Simulation-Based Experimental Teaching In Software Engineering,
2026
Software College of Northeastern University, Shenyang 110169, China
Iterative Evolution And Innovation Of Simulation-Based Experimental Teaching In Software Engineering, Jun Guo, Yixian Liu, Lianbo Ma, Jian Liu, Chunyan Xu
Journal of System Simulation
In view of the structural disconnection between talent training and industry needs caused by the limitations of traditional computer experiment teaching in scenario authenticity, technological frontier, interdisciplinary integration, and student subjectivity, this paper proposed and practiced a new simulation-based experimental teaching system deeply integrating Chinese educational wisdom. Taking "incremental progress and learning by guided inquiry" as the core philosophy, through a four-in-one paradigm transformation of "task modularization, scenario virtualization, technological frontier, and integration deepening", this paper promoted the teaching to shift from closed skill verification to open engineering innovation and constructed a complete implementation path including "closed-loop iterative teaching process" …
Robot Friction Force Compensation Algorithm Integrating Temperature And Speed Factors,
2026
Ningbo Institute of Materials Technology & Engineering, Chinese Academy of Sciences, Ningbo 315201, China; Ningbo Cixi Institute of Biomedical Engineering, Ningbo 315300, China
Robot Friction Force Compensation Algorithm Integrating Temperature And Speed Factors, Jinwang Lü, Ankai Ying, Ming Li, Tao Song, Jie Zhang, Fanghui Qiu, Changcheng Shi, Guokun Zuo, Jialin Xu
Journal of System Simulation
Insufficient friction force compensation accuracy degrades motion smoothness, stability, and assistive compliance of elbow joint rehabilitation robots. To address this issue, an improved Stribeck friction force model integrating temperature and speed factors was proposed. The model employed an exponentially decaying friction factor to describe the characteristic that the increase rate of friction force slowed down with the rise of the robot's operating speed and designed a viscous function considering temperature effects to suppress friction force fluctuations caused by temperature changes. Experimental results indicate that the model achieves stable friction force compensation under different operating states of the robot and has …
Designing For Fitness And Resilience In Human Artificial Intelligence Systems,
2026
University of South Florida
Designing For Fitness And Resilience In Human Artificial Intelligence Systems, Thomas R. Gill
USF Tampa Graduate Theses and Dissertations
Over the last decade, new artificial intelligence models, frameworks, and applications have emerged that have radically changed the socio-technical landscape. These new technologies represent both great opportunities and great potential risks. Due to the recency of their emergence, there is little known about the longevity and long-term repercussions of artifacts powered by new artificial intelligence technology. In this dissertation, I evaluate A.I. and A.I.-based artifacts through the lens of the fitness-utility model, a tool developed by Gill and Hevner (2013) for the evaluation of an artifact's ability to survive and reproduce over long time horizons. In so doing, I also …
Where Evidence-Based Medicine Meets Ai: Promise, Pitfalls, And Practice,
2026
Thomas Jefferson University
Where Evidence-Based Medicine Meets Ai: Promise, Pitfalls, And Practice, Sangil Lee, Joshua Davis, Ken Milne, Christina Shenvi, Lars K. Beattie, Martin Wegman, Laura Melville, Richard D. Shih, Bryan Kane
Department of Emergency Medicine Faculty Papers
No abstract provided.
Preface Of National Think Tank In Science And Technology: Ai Empowers Scientific Research,
2026
Chinese Academy of Sciences
Preface Of National Think Tank In Science And Technology: Ai Empowers Scientific Research
Bulletin of Chinese Academy of Sciences (Chinese Version)
No abstract provided.
Disciplinary System Of Artificial Intelligence: Connotation, Architecture, And Development Suggestions,
2026
Chinese Academy of Sciences, Beijing 100864, China
Disciplinary System Of Artificial Intelligence: Connotation, Architecture, And Development Suggestions, Academic Divisions Of The Chinese Academy Of Sciences Discipline Group Of Advisory Project On Ai-Empowered Scientific Research
Bulletin of Chinese Academy of Sciences (Chinese Version)
The discipline of artificial intelligence studies the theories, methods, systems, applications, enabling functions, ethics, and governance of artificial intelligence, and is a typical interdisciplinary field. With the rapid development of artificial intelligence in recent years, its disciplinary connotations and system architecture urgently require renewed examination. Based on the analysis of development trends of artificial intelligence, this paper elucidates the connotations of the AI discipline from four perspectives: theoretical methods, forms of intelligence, disciplinary integration, and application empowerment. It further proposes a disciplinary system framework for artificial intelligence comprising foundational supporting disciplines, core body of knowledge, major forms of intelligence, and …
Artificial Intelligence Empowers Particle Physics And Nuclear Physics: From Fundamental Research To Major Applications,
2026
Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
Artificial Intelligence Empowers Particle Physics And Nuclear Physics: From Fundamental Research To Major Applications, Yifang Wang, Yuan He, Yao Huang, Wanbing He, Yi Jiao, Congqiao Li, Ke Li, Beijiang Liu, Yingqi Ma, Yugang Ma, Longgang Pang, Fazhi Qi, Sichao Tan, Chunpeng Wang, Meng Wang, Xiaoheng Xu, Xing Xu, Zhentang Zhao, Yingxun Zhang, Zhengde Zhang, Hongwei Zhao, Lina Zhao
Bulletin of Chinese Academy of Sciences (Chinese Version)
Particle physics and nuclear physics are core foundational disciplines for exploring the fundamental structure of matter and the origin of the universe. The deep integration of artificial intelligence (AI) technology is providing entirely new pathways to address systemic challenges such as the processing of massive amounts of multimodal data, the realization of extreme experimental conditions, bottlenecks in theoretical calculations, and the intelligent control of large-scale scientific facilities. The article systematically elaborates on how AI deeply empowers particle physics and nuclear physics, particularly in major application scenarios such as research on the fundamental structure and origin of mass of matter, the …
Consolidating Chemical Substance Creation Capability Through Ai For Science-Enabled Innovation Equity,
2026
National Key Laboratory of Precision and Intelligent Chemistry, University of Science and Technology of China, Hefei 230026, China
Consolidating Chemical Substance Creation Capability Through Ai For Science-Enabled Innovation Equity, Mengchu Jin, Wandong Wang, Jun Zhang, Yi Luo, Zaiku Xie, Jinlong Yang, Jun Jiang
Bulletin of Chinese Academy of Sciences (Chinese Version)
AI for Science (hereinafter referred to as AI4S) is driving profound changes in the paradigm of scientific research. Chemistry, as a central discipline for creating new substances and supporting major national strategic needs such as energy, health, dual carbon goals, advanced manufacturing, and ecological governance, is an important application scenario of AI4S. At present, innovation in the discipline of chemistry by young researchers still faces knowledge silos, capability silos, and resource silos: the accumulation of professional knowledge requires years of effort, frontier knowledge is highly differentiated, experimental capabilities are difficult to reuse, and high-end resources are difficult to coordinate, which …
