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Articles 361 - 390 of 3920

Full-Text Articles in Computer Sciences

Research On Robot Path Planning Based On Improved Harris Hawks Algorithm, Yuxin Bai, Zhenya Chen, Ruitao Shi, Weitao Su, Zhuoqiang Ma, Shangjin Yang Mar 2025

Research On Robot Path Planning Based On Improved Harris Hawks Algorithm, Yuxin Bai, Zhenya Chen, Ruitao Shi, Weitao Su, Zhuoqiang Ma, Shangjin Yang

Journal of System Simulation

Abstract: In order to improve the convergence accuracy of the HHO algorithm, this paper proposes a GSHHO(gold sine harris hawks optimization) algorithm based on multi-strategies. An infinite iterative chaotic map is used to initialize the population, and an elite reverse learning strategy is used to improve population quality; A convergence factor adjustment strategy is used to recalculate prey energy, balancing the global exploration and local development capabilities of the algorithm; In the development phase of Harris Eagle, the golden sine strategy was introduced to replace the original position update method and improve the local development ability of the algorithm; Experiments …

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Fine-Grained Traffic Flow Inference Model Based On Dynamic Back Projection Network, Ming Xu, Guangyao Qi, Geqi Qi Mar 2025

Fine-Grained Traffic Flow Inference Model Based On Dynamic Back Projection Network, Ming Xu, Guangyao Qi, Geqi Qi

Journal of System Simulation

Abstract: To solve the problem of large errors in the inference results of existing fine-grained urban flow inference models in complex traffic areas, a fine-grained traffic flow inference model based on dynamic back-projection network is proposed. The multi-dimensional interaction between the input coarse-grained traffic flow and external factors is calculated, and the interaction results are dynamically and adaptively fused with the coarse-grained traffic flow, so that the features can interact and adjust each other to assist model reasoning. Combining deep convolution and self-attention mechanism to learn local information and global information, and improve the understanding of input data by subsequent …

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Parallel Task Transmission And Processing Optimization Scheme For Uav-Assisted Internet Of Vehicles, Chao Yang, Ruiqun Zheng, Zhen Li, Hongwei Zhang, Yanqun Tang, Dongze Li Mar 2025

Parallel Task Transmission And Processing Optimization Scheme For Uav-Assisted Internet Of Vehicles, Chao Yang, Ruiqun Zheng, Zhen Li, Hongwei Zhang, Yanqun Tang, Dongze Li

Journal of System Simulation

Abstract: To address the increasing of computation demands of internet of vehicles (IoV) users due to the sudden traffic congestion, unmanned aerial vehicles (UAVs) are introduced to the intelligent transportation systems (ITS) to construct an UAV-assisted IoV network. The UAV limited energy and computing resources lead to the current traditional UAV coverage strategy with one by one less efficiency. We propose a parallel task transmission and processing optimization strategy, considering the line-of-sight communication links and fast moving characteristics of UAV. After receiving the tasks from vehicles in the service point, UAV can fly to the next point and perform task …

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Research On Improved A* Algorithm Path Planning Based On Global Key Point Extraction, Guijuan Lin, Zihan Li, Yu Wang Mar 2025

Research On Improved A* Algorithm Path Planning Based On Global Key Point Extraction, Guijuan Lin, Zihan Li, Yu Wang

Journal of System Simulation

Abstract: To address the limitations of the traditional A* algorithm in large and complex scenes, including traversing a large number of nodes, long computation times, and susceptibility to U-shaped traps, this paper proposes an improved A* algorithm incorporating the jump point search (JPS) concept and image processing techniques to extract key points from the global map. The proposed method preprocesses the global map to identify corner points located one grid diagonally from obstacles, constructs a key point list, and replaces the nodes traditionally traversed by the A* algorithm with these global key points, significantly reducing computational overhead. The neighbor nodes …

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Real-Time Nonlinear Economic Model Predictive Control Of Wind Energy Conversion System, Wenwen Wang, Xiangjie Liu, Xiaobing Kong Mar 2025

Real-Time Nonlinear Economic Model Predictive Control Of Wind Energy Conversion System, Wenwen Wang, Xiangjie Liu, Xiaobing Kong

Journal of System Simulation

Abstract: To address the new challenges of economic control and real-time requirements in wind energy conversion systems (WECS), this study proposes a nonlinear economic model predictive control (NEMPC) strategy. This strategy aims to maximize power generation and while reducing fatigue loads on critical structures, such as towers and gearboxes. Additionally, a moving horizon estimator (MHE) has been designed to provide an effective initialization for optimization. By exploiting the similarity of nonlinear programs between adjacent sampling moments, the algorithm achieves real-time iterative (RTI) solutions. Using a 5 MW wind turbine as the research object, the proposed strategy is implemented in the …

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Design And Verification Of Display And Control System Based On Mbse And Vaps For Civil Helicopter, Xi Cao, Bo Liu, Bingzhi Su, Tao Nie Mar 2025

Design And Verification Of Display And Control System Based On Mbse And Vaps For Civil Helicopter, Xi Cao, Bo Liu, Bingzhi Su, Tao Nie

Journal of System Simulation

Abstract: Aiming at the challenges of difficulties in tracing requirements, detecting interaction design defects, and achieving early system design verification, this paper proposes a design and verification for the display and control system (DCS) of civil helicopters based on model-based systems engineering (MBSE) and VAPS. The method begins with capturing stakeholder requirements to form system requirements, followed by the allocation of these requirements to system use cases. Black-box activity diagrams and sequence diagrams are constructed to conduct "requirement-function analysis" from the top down, describing the functional flow of the DCS. A running black-box statechart diagram is further established to verify …

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Cae Simulation Optimization Method Based On Dynamic Coupling Model, Xue Chen, Jianwen Cao Mar 2025

Cae Simulation Optimization Method Based On Dynamic Coupling Model, Xue Chen, Jianwen Cao

Journal of System Simulation

Abstract: In order to solve the optimization problem of designing complex equipment under multi-factor coupling scene, a CAE simulation optimization method based on dynamic coupling model and multibranch parallel inference strategy is proposed. The dynamic hierarchical DEVS model is used to construct the automatic coupling model from pre-processing, numerical solution and post-processing phases of CAE software adaptively. Aiming at the key parameters of CAE model, multi-branch instance models with multi-factor constraints are constructed based on greedy algorithm. The multi-task parallel inference strategy is used to compute the multi-branch simulation results efficiently. The scheme optimization is realized based on the evaluation …

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Vibration Simulation And Multivariate Statistical Analysis Method Of Composite Structures, Bo Guo, Ming Tie, Wenhui Fan Mar 2025

Vibration Simulation And Multivariate Statistical Analysis Method Of Composite Structures, Bo Guo, Ming Tie, Wenhui Fan

Journal of System Simulation

Abstract: To investigate the natural frequency characteristics of composite laminates under parametric uncertainties and the different degree of influence of these parameters on the natural frequency under different boundary conditions and different vibration orders, a two-dimensional anisotropic medium-thick plate material model and a three-dimensional anisotropic cylindrical thin-shell material vibration model are established. Aiming at the uncertainty of structural parameters of these composite materials, the composite material vibration simulation and multivariate statistical analysis software are developed to simulate the structural vibration of composite materials. A multivariate statistical analysis method for natural frequency uncertainty of composite materials is presented. Through principal component …

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An Intelligent Ambulance Regulation Model Based On Online Reinforcement Learning Algorithm, Lei Zhang, Xuechao Zhang, Chao Wang, Xianglei Bo Mar 2025

An Intelligent Ambulance Regulation Model Based On Online Reinforcement Learning Algorithm, Lei Zhang, Xuechao Zhang, Chao Wang, Xianglei Bo

Journal of System Simulation

Abstract: In emergency scenarios where ambulances are used to evacuate casualties, it is necessary to fully coordinate the rescue capability of the ambulance with the real-time status of the casualties in the scenario to achieve the best rescue results. Such problems are generally non-deterministic polynomial problems, and the traditional deterministic scheduling algorithms are less effective. This paper aimed at the modeling research of the real-time regulation of ambulances in emergency scenarios, an online reinforcement learning DNQ algorithm frameworks based on the data enhancement method is proposed and applied to the solution of the ambulances control model. To solve the problems …

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Research On Pedestrian Avoidance Strategy For Agv Based On Deep Reinforcement Learning, He Wang, Jianing Xu, Guangyu Yan Mar 2025

Research On Pedestrian Avoidance Strategy For Agv Based On Deep Reinforcement Learning, He Wang, Jianing Xu, Guangyu Yan

Journal of System Simulation

Abstract: To ensure the safety and comfort of pedestrians during Automated Guided Vehicle (AGV) obstacle avoidance in smart factory environments, a deep reinforcement learning-based end-to-end obstacle avoidance method is proposed. The YOLOv8 module is introduced to extract pedestrian pose information, and a visual-based state space is designed. A reinforcement learning mechanism is formulated based on personal space theory, penalizing AGV behaviors such as entering pedestrian comfort space and collisions. A virtual simulation system is constructed, utilizing PPO algorithm along with LSTM network layer for obstacle avoidance strategy training and simulation experiments. Simulation results indicate that this obstacle avoidance strategy, under …

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City Regional Traffic Flow Prediction Based On Spatiotemporal Multi-View Attention Residual Network, Jing Chen, Guowei Yang, Zhaochong Zhang, Wei Wang Mar 2025

City Regional Traffic Flow Prediction Based On Spatiotemporal Multi-View Attention Residual Network, Jing Chen, Guowei Yang, Zhaochong Zhang, Wei Wang

Journal of System Simulation

Abstract: However, efficiently and comprehensively capturing the complex spatiotemporal correlations within urban traffic flow presents a key challenge. Existing research methods struggle to fully capture these spatiotemporal dependencies. To address these issues, we propose a novel end-to-end deep learning framework called the spatiotemporal multi-view attention residual network (ST-MVAR) for predicting traffic flow in urban areas. we integrate the proximity, periodicity, trend, and external factors of traffic flow as inputs to the network. This network employs skip connections to form a multi-layer nested residual network structure. Additionally, we design a Multi-View Extension module to capture spatial dependencies of traffic flow at …

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Economic Optimal Scheduling Of Microgrid Considering Elastic Recovery, Jianghong Chen, Kanghao Shi, Jiahui Hu, Xiaohan Zhao Mar 2025

Economic Optimal Scheduling Of Microgrid Considering Elastic Recovery, Jianghong Chen, Kanghao Shi, Jiahui Hu, Xiaohan Zhao

Journal of System Simulation

Abstract: To enhance the ability of microgrids (MGs) to withstand extreme disaster events, this paper proposes a multi-objective scheduling model considering resilience restoration and economic performance, based on the traditional concepts of power system resilience and reliability. Resilience is specifically quantified. The model integrates energy storage into the objective function and includes reliability indicators as constraints, building on traditional microgrid economic dispatch. The optimization problem is solved using an improved white shark optimizer (WSO) and multi-objective fuzzy programming, where different weights are assigned to each objective function, and the optimal weights are determined through case studies. A microgrid scheduling scheme …

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Three-Way Decision Clustering Algorithm Fusion Of Mutant Fireflies Algorithm, Zhaobin Li, Jun Ye, Haoyan Zhou, Yixin Wang, Yuzhen Han Mar 2025

Three-Way Decision Clustering Algorithm Fusion Of Mutant Fireflies Algorithm, Zhaobin Li, Jun Ye, Haoyan Zhou, Yixin Wang, Yuzhen Han

Journal of System Simulation

Abstract: To address problems such as the premature phenomenon in the three-way clustering algorithm caused by the random selection of initial cluster centers and the need for repeated experiments to determine the value of q in the q-nearest neighbor concept, a three-way clustering algorithm optimized by a variant of the firefly algorithm is proposed. The firefly algorithm is employed to solve the problem of sensitivity to initial cluster centers. The target function value is taken as the brightness intensity of firefly to search the clustering center point, and the optimal solution is taken as the clustering center of the algorithm …

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Tohf: A Feature Extractor For Resource-Constrained Indoor Vslam, Ruoqing Li, Yaochi Zhao, Zhuhua Hu, Wenlu Qi, Guangfeng Liu Mar 2025

Tohf: A Feature Extractor For Resource-Constrained Indoor Vslam, Ruoqing Li, Yaochi Zhao, Zhuhua Hu, Wenlu Qi, Guangfeng Liu

Journal of System Simulation

Abstract: To address the issues of sensitivity to texture and lighting variations, excessive local dependence caused by feature point redundancy, and storage overhead under hardware resource constraints in existing VSLAM feature extractors in indoor environments, We propose the Texture- Oriented and Homogenized FAST Feature Extractor (TOHF), which integrates HVS (Human Visual System) for enhanced texture analysis. TOHF employs a two-stage thresholding strategy and dynamically adjusts feature point distribution, balancing computational efficiency and storage needs. We conducted experimental verification based on the ORB-SLAM3 framework on dataset from resource-limited device and the EuRoc dataset, focusing on matching rate, reprojection error, absolute trajectory …

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Electric Vehicle Dispatching Strategy And Incentive Evaluation Based On Virtual Energy Storage, Shuo Chen, Hao Hu, Huimin Fang, Haiwei Wang, Xiaolong Chen, Chengcheng Mei, JiaʹNan Zhu, Qian Ai Mar 2025

Electric Vehicle Dispatching Strategy And Incentive Evaluation Based On Virtual Energy Storage, Shuo Chen, Hao Hu, Huimin Fang, Haiwei Wang, Xiaolong Chen, Chengcheng Mei, JiaʹNan Zhu, Qian Ai

Journal of System Simulation

Abstract: To address the multifaceted challenges arising from the widespread integration of electric vehicles into the power grid, harnessing the dispatchability features of electric vehicles becomes imperative. This paper based on a virtual energy storage aggregation model, optimizes the charging scheduling of electric vehicles and assesses their charging incentives through a composite weighting methodology. It establishes a framework for the participation of flexible loads in distribution network scheduling, formulates a second-order cone relaxation optimal power flow model, and develops dispatch strategies. By quantifying the contribution of electric vehicles concerning their flexibility and system stability, and simulating user charging preferences using …

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Visual Slam Algorithm Based On Feature Point Selection In Dynamic Scenes, Limei Jiang, Xinwei Chen Mar 2025

Visual Slam Algorithm Based On Feature Point Selection In Dynamic Scenes, Limei Jiang, Xinwei Chen

Journal of System Simulation

Abstract: To address low positioning accuracy and robustness in traditional visual SLAM algorithms under dynamic conditions, this paper proposes an improved dynamic SLAM algorithm based on feature point selection. Built upon the ORB-SLAM3 framework, it incorporates dynamic region partitioning and feature point filtering. The dynamic region partitioning module utilizes an enhanced RT-DETR object detection algorithm to detect dynamic objects in the images and divides the dynamic regions based on the detection boxes. The feature point selection module utilizes epipolar constraints and optical flow methods to filter out feature points on moving objects, retaining stationary dynamic objects and background points within …

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Reinforcement Learning Modeling Of Missile Penetration Decision Based On Combat Simulation, Bin Zhang, Yonglin Lei, Qun Li, Yuan Gao, Yong Chen, Jiajun Zhu, Chenlong Bao Mar 2025

Reinforcement Learning Modeling Of Missile Penetration Decision Based On Combat Simulation, Bin Zhang, Yonglin Lei, Qun Li, Yuan Gao, Yong Chen, Jiajun Zhu, Chenlong Bao

Journal of System Simulation

Abstract: Penetration capability is a primary measure of missile systems. In response to the shortcomings of traditional knowledge-based decision-making methods that are difficult to adaptively evolve, an intelligent penetration decision-making based on combat simulation and DRL is proposed. A missile intelligent decision-making training environment is constructed based on the WESS system. Taking missile maneuver penetration decision-making as an example, a maneuver penetration decisionmaking network model is designed and trained based on the SAC-discrete algorithm and the test of intelligence is conducted. Experimental results show that the intelligent decision model derived from machine learning has a better combat outcome than traditional …

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Research On Transformer Fault Diagnosis Method Based On Digital Twin, Lun Jiang, Dajiang Wang, Wenlei Sun, Shenghui Bao, Han Liu, Saike Chang Mar 2025

Research On Transformer Fault Diagnosis Method Based On Digital Twin, Lun Jiang, Dajiang Wang, Wenlei Sun, Shenghui Bao, Han Liu, Saike Chang

Journal of System Simulation

Abstract: Aiming at the inability of existing intelligent algorithms for transformer fault diagnosis to quickly and efficiently identify transformer faults, resulting in fault misdetection and untimely detection, this paper proposes a transformer fault diagnosis method using the improved sparrow optimization algorithm to optimize the two-layer fault diagnostic model of XGBoost combined with the digital twin technology. The method adopts advanced sensors to collect oil and gas data and temperature data of the transformer, uses 5G module to transmit the real-time data to the digital twin system. The system monitors the temperature data in real-time by setting the equipment alarm threshold; …

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Research On Air Target Threat Assessment Technology Based On Deep Learning, Dawei Jiang, Yangyang Dong, Lidong Zhang, Xiao Lu, Chunxi Dong Mar 2025

Research On Air Target Threat Assessment Technology Based On Deep Learning, Dawei Jiang, Yangyang Dong, Lidong Zhang, Xiao Lu, Chunxi Dong

Journal of System Simulation

Abstract: In order to realize the effective assessment of air combat targets, a deep learning-based air target threat assessment method is proposed. According to threat characteristics of the air target, the threat attributes of air target faced by electronic countermeasure operation are analyzed from the two perspectives of platform layer and equipment layer, the air target threat assessment index system is constructed, and the air target threat assessment index data set is established. Based on convolutional neural network, a residual structure is introduced to optimize the network, a threat assessment model is established, and the threat ranking of air targets …

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Multi-Strategy Hybrid Mountain Gazelle Optimizer For Robot Path Planning, Xu Jin, Yuanbin Mo Mar 2025

Multi-Strategy Hybrid Mountain Gazelle Optimizer For Robot Path Planning, Xu Jin, Yuanbin Mo

Journal of System Simulation

Abstract: Aiming at the problems of local optimum and premature convergence in the design of optimization path of robot navigation system, a multi-strategy hybrid MGO(HMGO) improved algorithm based on the mountain gazelle optimizer(MGO) is proposed. The algorithm uses the quasi-reverse learning strategy to optimize the population initialization ensuring its diversity, introduces the dynamic adaptive density factor to adjust the parameters of the optimization mechanism, and integrates arithmetic optimization and sine-cosine strategies for random perturbations. Through ablation experiments, 13 benchmark test functions, and simulation experiments on the solution of two-dimensional and threedimensional space robot path planning problems, the results demonstrate that …

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Improved Bidirectional A* Quadratic Path Planning Algorithm For Mobile Robots, Jiongyi Li, Qiang Li, Xinwen Zhang, Myo Htet Zin, Yongbin Cai Feb 2025

Improved Bidirectional A* Quadratic Path Planning Algorithm For Mobile Robots, Jiongyi Li, Qiang Li, Xinwen Zhang, Myo Htet Zin, Yongbin Cai

Journal of System Simulation

Abstract: Aiming at the problems of the traditional A* algorithm, such as the unhoped intersection between the planned path and the obstacles, the planned path has many inflection points and the search time is long, an improved bidirectional A* quadratic path planning algorithm for the indoor environments is proposed. Through the expansion of the map, the intersection between the planned path and the obstacle is solved. By new heuristic functions and bidirectional expansion methods, the search speed and accuracy of the bidirectional A* algorithm are improved. Turning cost function and adaptive weight are introduced to reduce the number of turning …

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Collaborative Optimization Problem Of Dynamic Pre-Maintenance And Green Scheduling, Yuyan Jiang, Ning Ma, Yan Li, Rumeijiang Gan, Fuyu Wang Feb 2025

Collaborative Optimization Problem Of Dynamic Pre-Maintenance And Green Scheduling, Yuyan Jiang, Ning Ma, Yan Li, Rumeijiang Gan, Fuyu Wang

Journal of System Simulation

Abstract: For the traditional flexible job shop scheduling problem, a joint optimization of machine dynamic pre-maintenance and green scheduling is considered to establish an integrated optimization model with the optimization objectives of minimizing maximum completion time, total carbon emissions, and total cost. An improved NSGA-II algorithm is proposed to solve the model. A three-layer encoding method based on process, machine, and pre maintenance is adopted to design a one-step decoding scheme that considers process allocation, machine selection, and machine pre-maintenance strategies. The algorithm improves the elitist retention strategy, designs an adaptive crossover mutation function with algebraic changes, and a mutation …

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Trajectory Optimization Of Robotic Arm Based On Improved Simulated Annealing Genetic Algorithm, Qiang Xu, Jianlei Xu, Yanhai Hu, Haihui Chen, Xing Zhang, Zhaohui Xing Feb 2025

Trajectory Optimization Of Robotic Arm Based On Improved Simulated Annealing Genetic Algorithm, Qiang Xu, Jianlei Xu, Yanhai Hu, Haihui Chen, Xing Zhang, Zhaohui Xing

Journal of System Simulation

Abstract: To optimize the working trajectory of the robotic arm, a modified simulated annealing genetic algorithm is proposed. Comprehensively considering the operating requirements and performance characteristics of the robotic arm, the five-order polynomial interpolation method is used to plan a smooth motion trajectory in the joint space. The penalty function method is used to handle the individuals that do not meet the constraint conditions, and the fitness function is recalibrated by the dynamic linear calibration method. An adaptive adjustment mechanism for crossover probability and variation probability is set to modify the genetic algorithm. The cooling idea of the simulated annealing …

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An Algorithm For Cloud-Based Web Service Combination Optimization Through Plant Growth Simulation, Qiang Li, Huawei Qin, Bingqin Qiao, Ruifang Wu Feb 2025

An Algorithm For Cloud-Based Web Service Combination Optimization Through Plant Growth Simulation, Qiang Li, Huawei Qin, Bingqin Qiao, Ruifang Wu

Journal of System Simulation

Abstract: In order to improve the efficiency of cloud-based web services, an improved plant growth simulation algorithm scheduling model. This model first used mathematical methods to describe the relationships between cloud-based web services and the constraints of system resources. Then, a lightinduced plant growth simulation algorithm was established. The performance of the algorithm was compared through several plant types, and the best plant model was selected as the setting for the system. Experimental results show that when the number of test cloud-based web services reaches 2 048, the model being 2.14 times faster than PSO, 2.8 times faster than the …

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Research On Flexible Integrated Scheduling Under Stochastic Processing Times Based On Improved D3qn Algorithm, Xiang Li, Xiaoyu Ren, Yongbing Zhou, Jian Zhang Feb 2025

Research On Flexible Integrated Scheduling Under Stochastic Processing Times Based On Improved D3qn Algorithm, Xiang Li, Xiaoyu Ren, Yongbing Zhou, Jian Zhang

Journal of System Simulation

Abstract: Aiming at the problem of time uncertainty in discrete manufacturing workshops, we construct an integrated scheduling mathematical model with the optimization objective of minimizing the maximum completion time based on the consideration of equipment and process constraints, and propose an improved dual-competitive deep Q-network algorithm (ID3QN) to solve the flexible integrated scheduling problem under stochastic working hours. The levels of process, machine, and overall scheduling are designed as features. Eight composite scheduling rules are formed as the action space by combining process rules based on processing times, processing sequences, and process structure tree, along with machine rules relevant to …

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Research On The Target Allocation Method For Air Defense And Anti-Missile Defense Of Naval Ships, Shuaidi Fei, Changlong Cai, Fei Liu, Minghui Chen, Xiaoming Liu Feb 2025

Research On The Target Allocation Method For Air Defense And Anti-Missile Defense Of Naval Ships, Shuaidi Fei, Changlong Cai, Fei Liu, Minghui Chen, Xiaoming Liu

Journal of System Simulation

Abstract: To solve the problems of multiple types of state information and correlation of time-series state information encountered in the dynamic weapon target assignment problem, a dynamic weapon target assignment method based on an improved deep reinforcement learning algorithm is proposed. A multiinput assignment model of target missile-interceptor unit, interceptor unit, and defense unit under multiwave target and multi-phase is constructed. A multi-input state space is designed, and a Markov decision process is established in conjunction with the problem model. A feature extraction network combining multi-input information processing and gated recurrent network is designed, which improves the ability to extract …

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Combat Effectiveness Evaluation Of Air Defense Missile Weapon System Based On Rbf Neural Network, Peng Zhang, Ke Feng, Jiancheng Gong, Xiaoqiang Yang, Jinxing Shen Feb 2025

Combat Effectiveness Evaluation Of Air Defense Missile Weapon System Based On Rbf Neural Network, Peng Zhang, Ke Feng, Jiancheng Gong, Xiaoqiang Yang, Jinxing Shen

Journal of System Simulation

Abstract: A combat effectiveness evaluation method based on RBF neural network is proposed to address the problems of high dimensionality, high complexity, and subjective evaluation methods in current air defense missile weapon systems. A combat effectiveness index system for air defense missile weapon systems has been constructed by analyzing the OODA environmental combat theory. The RBF neural network model simulation is implemented using MATLAB, and several methods such as BP, PCABP, and Elman neural network are compared and verified through simulation. The simulation results show that the predicted evaluation results of the RBF neural network model are closer to the …

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Dynamic Loading Simulation Method For Large-Scale Spiking Neural Network, Jiawei Shen, Daye Cai, Guoqing Yang, Pan Lü, Hong Li Feb 2025

Dynamic Loading Simulation Method For Large-Scale Spiking Neural Network, Jiawei Shen, Daye Cai, Guoqing Yang, Pan Lü, Hong Li

Journal of System Simulation

Abstract: To address the problem of high GPU memory requirements in large-scale spiking neural network simulation, a dynamic loading simulation method for large-scale spiking neural networks is proposed. This method uses data movement at the sub-network granularity and utilizes the host memory as a larger memory pool to reduce the limitation of GPU memory on the model simulation scale, enabling large-scale spiking neural network simulation on a single GPU computer. The pipeline acceleration technique is adopted to reduce the impact of data movement on simulation speed. The simulation of a million-scale neural network is achieved in a single GPU experimental …

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Design And Simulation Analysis Of Guidance Law For Boost Phase Interceptor Missile, Xu Zhang, Peng Zeng, Xu Li, Xuehe Zheng, Jianheng Xue, Chao Wang Feb 2025

Design And Simulation Analysis Of Guidance Law For Boost Phase Interceptor Missile, Xu Zhang, Peng Zeng, Xu Li, Xuehe Zheng, Jianheng Xue, Chao Wang

Journal of System Simulation

Abstract: The intercept time window in the boost phase is very short, which requires the missile to have high speed and high acceleration capability, at the same time, because the target ballistic missile is still accelerating in the boost phase, the guidance scheme of the interceptor missile needs to have the ability to cope with the characteristics of the booster phase interceptor missile. The trajectory simulation model is established, and the guidance law of the boost phase interceptor missile in the initial guidance, midguidance and final guidance stage are designed in detail according to the performance of the guidance mechanism …

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Quadrotor Uav Path Planning Based On Rapidly-Exploration Directional Tree Algorithm, Shijun Hu, Hailiang Liu, Binglei Wang, Wenke Su Feb 2025

Quadrotor Uav Path Planning Based On Rapidly-Exploration Directional Tree Algorithm, Shijun Hu, Hailiang Liu, Binglei Wang, Wenke Su

Journal of System Simulation

Abstract: Aiming at the problems of low planning success rate, slow convergence speed, and suboptimal paths in the RRT algorithm for quadrotor UAV path planning of in complex environments, a directional exploration tree algorithm is proposed, which uses a directional sampling strategy to improve the directionality of the tree expansion, and by introducing an adaptive target adjustment strategy and a branch expansion strategy, the tree can expand quickly towards the target point while avoiding obstacles. The redundant points in the initial path are removed by the pruning process, and then the trajectory correction and smoothing process are performed on the …

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