Multi-Scale Modeling Method For Intelligent Unmanned Aerial Vehicle Swarm Combat,
2026
Army Command College, Nanjing 210008, China
Multi-Scale Modeling Method For Intelligent Unmanned Aerial Vehicle Swarm Combat, Yelei Zhu, Shoulin Shen, Jiang Zhu, Chuanhua Wen
Journal of System Simulation
Abstract: Intelligent unmanned aerial vehicle swarm combat exhibits multi-scale characteristics of microlevel tactical autonomy, meso-level resource constraints, and macro-level network collaboration. In view of the problem that a single-scale modeling method is difficult to simultaneously characterize individual decision-making details, resource flow process, and system collaboration mechanism, a multi-scale modeling method integrating multi-agent modeling, system dynamics, and complex network theory was proposed. By designing six formal coupling operators to achieve cross-layer information mapping, a time progression mechanism based on a master-slave clock and hybrid synchronization was established, and a proof of error boundedness was provided. A prototype system was implemented on …
Modeling And Simulation Of Efficient State Information Diffusion In Wireless Ad Hoc Networks,
2026
School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China
Modeling And Simulation Of Efficient State Information Diffusion In Wireless Ad Hoc Networks, Mengyao Jia, Shaozhu Gu, Junhan Wang, Denghao Wang, Du Xu, Xiaoning Zhang
Journal of System Simulation
Abstract: To solve the problems of significant communication overhead and limited real-time response capability in the traditional flooding-based state diffusion mechanism, an efficient diffusion algorithm based on regional partitioning and information compression was proposed. A multi-dimensional feature clustering method integrating geographic distance and link quality was used to achieve high-cohesion network partitioning through weighted Euclidean distance and the K-means algorithm; a dynamic selection mechanism for representative nodes was designed to conduct comprehensive scoring by combining the link quality and geographic centrality of nodes, realizing the efficient compression and aggregated transmission of regional information. Simulation results indicate that the algorithm significantly …
Research On Safety Monitoring System For Digital Twin Fully Mechanized Mining Face In Thin Coal Seams,
2026
Shandong Energy Group Beidou Tiandi Co., Ltd., Xi'an 710000, China; College of Electronic and Information Engineering, Shandong University of Science and Technology, Qingdao 266000, China
Research On Safety Monitoring System For Digital Twin Fully Mechanized Mining Face In Thin Coal Seams, Ya Liu, Zhaoyun Zhang, Cheng An, Canguang Zheng
Journal of System Simulation
Abstract: To solve the problems of opaque production processes, difficult expression of production information, and high difficulty in real-time model driving and safety monitoring in fully mechanized mining faces of thin coal seams, studying the use of digital twin technology and risk early warning models to solve beyond-visual-range visual production operations and safety monitoring control of the working face has important theoretical and practical value. This paper studied the construction methods of the digital twin system for fully mechanized mining faces in thin coal seams and discussed the construction of high-precision three-dimensional models, the real-time collection and processing conversion of …
Trajectory-Aware Dynamic Offloading For High-Mobility Vehicular Edge Systems,
2026
College of Computer and Data Science, Fuzhou University, Fuzhou 350116, China; Engineering Research Center of Big Data Intelligence, Ministry of Education, Fuzhou 350002, China; Fujian Key Laboratory of Network Computing and Intelligent Information Processing (Fuzhou University), Fuzhou 350116, China
Trajectory-Aware Dynamic Offloading For High-Mobility Vehicular Edge Systems, Haoran Xu, Zhiqin Huang, Youwu Hu, Zheyi Chen
Journal of System Simulation
Abstract: To address the problems of service interruptions, task failures, and resource waste caused by high mobility of intelligent vehicles (IVs) in vehicular edge computing (VEC), this paper proposes a trajectory-aware dynamic offloading (TADO) framework for high-mobility vehicular edge systems. A lightweight T-pattern trajectory-aware algorithm is designed to efficiently predict the next-hop road side unit (RSU) by mining spatio-temporal patterns from historical trajectories of vehicles, offering a forward-looking reference for offloading decisions. A joint optimization model is constructed, and a service interruption risk factor driven by trajectory prediction is introduced. An improved DRL method is developed. It takes the predicted …
Multi-Auv Pursuit Algorithm With Phased Guidance Based On Maddpg,
2026
School of Information Engineering, Henan University of Science and Technology, Luoyang 471000, China
Multi-Auv Pursuit Algorithm With Phased Guidance Based On Maddpg, Sen Zhang, Sihang Shen, Xiaojie Sun, Jingping Shao, Shuaiqiang Guo, Yingjie Deng
Journal of System Simulation
Abstract: To address the problems such as low exploration and sampling efficiency and sparse rewards in the early training stage under the complex target pursuit environment of multiple AUVs based on MADDPG, a phased-guidance curriculum MADDPG (PGC-MADDPG) algorithm was proposed. The pursuit task was divided into two phases, i.e., target tracking and encircling, through curriculum learning. In the target tracking phase, an experience strategy based on the APF method was introduced as a guidance item to provide prior knowledge of the target direction and accelerate the AUV training speed. After entering the encircling phase, the APF guidance item was removed, …
Study On Trajectory Optimization Of Spray Painting Robot Based On Improved Sparrow Search Algorithm,
2026
State Key Laboratory of Digital and Intelligent Technology for Unmanned Coal Mining, Anhui University of Science & Technology, Huainan 232001, China; College of New Energy and Intelligent Connected Vehicle, Anhui University of Science & Technology, Hefei 231131, China
Study On Trajectory Optimization Of Spray Painting Robot Based On Improved Sparrow Search Algorithm, Jie Yang, Zhenkai Xiong, Longyan Wang
Journal of System Simulation
Abstract: To address the challenges posed by the complex working environment to the trajectory planning of the spray painting robot, a multi-strategy integrated sparrow search algorithm (MISSA) was proposed with the dual optimization objectives of time efficiency and motion smoothness. The 3-5-3 polynomial interpolation method was adopted to design the trajectory curve, aiming to ensure continuous angular displacement, angular velocity, and angular acceleration throughout the process. A multidimensional optimization problem with joint constraints was constructed using the total trajectory duration as the performance index. MISSA, which integrates refraction reverse learning, sine-cosine adaptive adjustment, and Cauchy mutation, was utilized to optimize …
Research On Multi-Objective Hybrid Flow-Shop Scheduling With Order Splitting,
2026
School of Mechanical Engineering, Jiangnan University, Wuxi 214122, China
Research On Multi-Objective Hybrid Flow-Shop Scheduling With Order Splitting, Junjie Yu, Weixi Ji, Chen Chen, Jingyu Lu, Chaoyang Zhang
Journal of System Simulation
Abstract: To address the order splitting multi-objective hybrid flow-shop scheduling problem (OSMOHFSP), a dual-objective optimization model was formulated with the objectives of minimizing makespan and total order tardiness. Fixed sub-batch specification constraints were incorporated to reflect common splitting limitations in actual production. A sub-batch generation strategy based on a candidate set of sub-batch specifications was designed to efficiently filter feasible splitting combinations, effectively reducing the search space dimensionality and computational complexity. A hybrid multi-objective metaheuristic algorithm integrating NSGA-II and SA was proposed. The global search capability was enhanced by constructing two crossover and four mutation operators. An improved SA embedding …
Ultra-Short-Term Photovoltaic Power Prediction Method Based On Spatio-Temporal Feature Enhancement Of Ground-Based Cloud Images,
2026
College of Electric Power, Inner Mongolia University of Technology, Hohhot 010080, China; Engineering Research Center of Large Energy Storage Technology, Ministry of Education, Hohhot 010080, China; Key Laboratory of Smart Control for New Energy Power System of Inner Mongolia Autonomous Region, Hohhot 010080, China
Ultra-Short-Term Photovoltaic Power Prediction Method Based On Spatio-Temporal Feature Enhancement Of Ground-Based Cloud Images, Zhiwei Kou, Fengyue Xin, Xiaoming Cui, Yu Yin, Feifan Li, Yongsheng Qi
Journal of System Simulation
Abstract: In view of the time lag in ground-based cloud image acquisition and the insufficient accuracy of existing photovoltaic power prediction models, an ultra-short-term photovoltaic power prediction method named spatial-temporal feature enhancement-ground-based cloud image-improved LSTM (STFE-GCI-ILSTM), which is based on spatio-temporal feature enhancement-ground-based cloud images-improved long short-term memory (LSTM) network was proposed. A ground-based cloud image prediction model with multi-scale spatio-temporal feature enhancement (STFE-GCI) was constructed. By spatial feature enhancement, temporal feature enhancement, and multi-scale feature fusion technologies, the deep spatio-temporal features of historical cloud image sequences were extracted to generate future predicted cloud image sequences, thereby eliminating the time …
Simulation Platform Based On Soc-Fpga Clusters For Cxl-Ethernet Heterogeneous Interconnection,
2026
Institute of Computing Technology, CAS, Beijing 100190, China; University of Chinese Academy of Sciences, Beijing 100049, China
Simulation Platform Based On Soc-Fpga Clusters For Cxl-Ethernet Heterogeneous Interconnection, Xu Zhang, Ke Liu, Mingyu Chen
Journal of System Simulation
Abstract: To address the difficulty of balancing simulation speed and topology flexibility when simulating large-scale, CXL-Ethernet heterogeneous interconnect datacenter scenarios with existing CXL simulation platforms, this paper presents CNetSim, a semi-physical simulation platform based on an SoC-FPGA cluster. The platform employs SoC-FPGA hardware to emulate endpoint nodes, leveraging their real processors and memory devices as well as FPGA-implemented CXL. mem protocol to support high-speed execution of standard Linux systems and real distributed applications. Meanwhile, it utilizes the flexible topology configuration capability of software simulation to implement CXL switched networks and inter-rack Ethernet interconnects based on DPDK on simulation servers. Simulation …
Optimization Of Convective Heat Transfer Parameters For Spindles Based On Finite Element Thermal Analysis,
2026
Air Force Engineering University, Xi'an 710051, China
Optimization Of Convective Heat Transfer Parameters For Spindles Based On Finite Element Thermal Analysis, Jiali Zhang, Haiping Liu, Qinsheng Jiang, Sina Dang
Journal of System Simulation
Abstract: In view of the low simulation accuracy of existing finite element models for thermal characteristics of spindles caused by ignoring the influences of geometric characteristics of convective surfaces and fluid flow patterns and often adopting constant temperature loading in the setting of convective heat transfer boundary conditions, this paper proposed an optimization method for convective heat transfer parameters of spindles based on finite element thermal analysis. Combined with the geometric shapes and spatial positions of various convective surfaces of the spindle system, the calculation criterion of the convective heat transfer coefficient was determined through dimensional analysis according to the …
Simulation And Optimization Of Task Offloading In Mine Edge Computing For Low-Concurrency Devices,
2026
School of Science, Jiangxi University of Science and Technology, Ganzhou 341000, China
Simulation And Optimization Of Task Offloading In Mine Edge Computing For Low-Concurrency Devices, Zhaolu Guo, Qianhui Liu
Journal of System Simulation
Abstract: With the advancement of mine intelligence, task offloading technology has become a core technology of mine edge computing (MEC). For edge computing systems deployed with mine low-concurrency devices (MLCD), a discrete-event simulation model for MEC task offloading oriented to MLCD was constructed to solve the collaborative optimization problem of task processing latency and load balancing of mine edge servers (MES). By dynamically simulating the queuing, transmission, and computation processes of tasks, the objective of minimizing task processing latency was achieved. An improved evolutionary algorithm, ISBT-EA, was proposed, which integrated a task-characteristic-driven initialization strategy and local search operators, enhancing the …
Prediction Of Industrial Concentration Parameters Based On Caudformer Model,
2026
School of Internet of Things Engineering, Jiangnan University, Wuxi 214122, China
Prediction Of Industrial Concentration Parameters Based On Caudformer Model, Kaipeng Xu, Yan Wang, Xin Zhang, Yang Liu, Zhenzhong Wang, Xiang Liu, Zhicheng Ji
Journal of System Simulation
Abstract: To solve the problems in the industrial concentration process of traditional Chinese medicine that traditional prediction methods are difficult to deal with complex characteristics such as nonlinearity, high-dimensional coupling, and highly skewed distribution and that existing deep learning models insufficiently consider causal relationships among variables, ignore frequency-domain periodic characteristics, and lack long-range dependency modeling capabilities, an improved multivariate time series prediction model CauDformer was proposed in this paper. Based on the iTransformer architecture, a causal multi-head self-attention mechanism (C-MHSA) was introduced to compulsorily constrain the dependency direction among variables by utilizing a lower triangular causal mask, guiding the model …
Constrained Assortment Optimization Under The Mixed-Logit Model,
2026
Singapore Management University
Constrained Assortment Optimization Under The Mixed-Logit Model, Hoang Giang Pham, Tien Mai
Research Collection School Of Computing and Information Systems
In this paper, we study the assortment optimization problem under the mixed-logit customer choice model. While assortment optimization has been a central topic in revenue management for decades, the mixed-logit model is widely regarded as one of the most general and flexible frameworks for modeling and predicting customer purchasing behavior. The assortment optimization problem is known to be NP-hard to be approximated to any constant factor, even in the unconstrained case. To address this challenge, we first explore the submodularity properties of a simplified version of the objective function to derive novel semi-constant factor approximation solutions for assortment problems under …
Improved Pbs Algorithm For Multi-Agent Path Planning Based On Conflict Guidance And Punishment Mechanism,
2026
Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650500, China
Improved Pbs Algorithm For Multi-Agent Path Planning Based On Conflict Guidance And Punishment Mechanism, Jinbao Zhang, Jianlin Mao, Chengze Qian, Guimi Sun, Kaixin Tong
Journal of System Simulation
Abstract: To address the bottleneck in which the priority-based search (priority-based search, PBS) algorithm for multi-agent path planning easily falls into conflict loops and generates invalid node expansions in complex scenarios, an improved algorithm based on conflict guidance and a punishment mechanism (improved PBS multi-agent path finding algorithm based on conflict guidance and punishment mechanism, CGP-PBS) was proposed. A conflict-guided node expansion mechanism was constructed; in high-level search, it comprehensively evaluated path cost and the number of conflicts, preferentially expanded child nodes with high potential for conflict resolution, and delayed the expansion of high-conflict nodes, thereby effectively compressing the search …
Adaptive Path Planning For Robotic Arms Integrating Rrt* And Apf,
2026
School of Intelligence Science and Technology, Xinjiang University, Urumqi 830017, China
Adaptive Path Planning For Robotic Arms Integrating Rrt* And Apf, Zhirun Chen, Jie Yuan, Erkenbieke Jia, Ningning Zhang, Chao Liu, Yushan Ye
Journal of System Simulation
To address the issues of large search space, low efficiency, and slow convergence of the RRT* algorithm in 3D path planning of robotic manipulators, an adaptive path planning algorithm integrating RRT* and APF is proposed. In the sampling phase, a Sobol sequence-based obstacle avoidance strategy and an APF adaptive-threshold, goal-biased sampling method are used to improve the quality of sampling points. During the expansion phase, sampling, attractive, and repulsive vectors are integrated, and adaptive weights are designed based on environmental information to generate a resultant force direction, thus enhancing the expansion guidance. For step size control, the obstacle repulsive potential …
Design Of Teaching Model For Simulation Engineering Comprehensive Practical Course,
2026
College of System Engineering, National University of Defense Technology, Changsha 410073, China
Design Of Teaching Model For Simulation Engineering Comprehensive Practical Course, Meigen Huang, Xin Zhou, Tian Jing, Tao Wang
Journal of System Simulation
To cultivate postgraduates' comprehensive engineering problem-solving ability to complex problems, based on Wittrock's generative learning theory and the agile systems engineering paradigm, this paper proposed an overall idea of curriculum construction reform promoted by the integration of teaching and research, independently developed an unmanned swarm attack and defense simulation experimental teaching platform, constructed a comprehensive practical case of "warship defense against unmanned aerial vehicle swarm attacks", and refined a relatively advanced and distinctive teaching model for the simulation engineering comprehensive practical course. This model effectively strengthens postgraduates' engineering problem-solving thinking for complex problems, stimulates their independent innovation ability, elevates …
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 …
Dynamic Analysis Of Flexible Mechanism With Lubrication Clearances Considering Uncertain Parameters,
2026
College of Mechanical and Electronic Engineering, Shandong University of Science and Technology, Qingdao 266590, China
Dynamic Analysis Of Flexible Mechanism With Lubrication Clearances Considering Uncertain Parameters, Xiulong Chen, Yi Sun, Aiguo Wang
Journal of System Simulation
This paper conducted a dynamic analysis on a seven-link mechanism suitable for a hybriddriven press, simultaneously considering lubrication clearances, interval parameters, and link flexibility. Based on the Lagrange equations of the first kind, the dynamic equations of the flexible mechanism with lubrication clearances under deterministic parameters were established; interval variables were introduced to establish a dynamic model considering interval parameters, and the Chebyshev interval algorithm and the Runge - Kutta method were used to solve the response interval curves of interval parameters such as clearances value, dynamic viscosity, and cross-sectional area. The results show that compared with the results under …
Energy Management Strategy For Hybrid Electric Buses Considering Vehicle Mass Variation,
2026
School of Traffic & Transportation Engineering, Central South University, Changsha 410075, China
Energy Management Strategy For Hybrid Electric Buses Considering Vehicle Mass Variation, Jinjun Tang, Shuaijie Zhang
Journal of System Simulation
The vehicle mass variation during the operation of buses affects power demand of the vehicle, which can result in poor performance of energy management strategies. To this end, a hybrid electric bus energy management strategy based on proximal policy optimization-adaptive simulated annealing (PPOASA) is proposed. ASA is introduced into PPO to perturb policy parameters according to policy entropy before the policy update, and the perturbed policies are adaptively accepted or rejected by employing the Metropolis criterion, thus improving the exploration capability of the policy and convergence stability. Experimental results show that the proposed method outperforms the charge depleting-charge sustaining (CD-CS) …
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 …
