Solving The Vehicle Routing Problem Based On Deep Reinforcement Learning,
2025
School of Internet Economics and Business, Fujian University of Technology, Fuzhou 350014, China
Solving The Vehicle Routing Problem Based On Deep Reinforcement Learning, Ming Jiang, Tao He
Journal of System Simulation
Abstract: The capacitated vehicle routing problem (CVRP) is a well-known combinatorial optimization challenge recognized as NP-hard due to its significant complexity. Building upon existing research, this paper introduces a novel end-to-end deep reinforcement learning approach based on a multi-pointer Transformer to tackle the CVRP. The proposed algorithm employs an invertible residual network in the encoder to encode input features, effectively reducing memory consumption. In the decoder, a multipointer network determines the probability distribution of solutions. To further enhance the performance of CVRP solutions, the algorithm leverages the symmetry in combinatorial optimization by implementing multi-trajectory parallel processing during both training …
Lane Detection In Dark Light Based On Instance Association,
2025
College of Software, Liaoning Technical University, Huludao 125105, China; OpenSafe Lab, Utcer(Jiangsu) Safety Technology Co. , Ltd, Suzhou 215100, China
Lane Detection In Dark Light Based On Instance Association, Yanji Jiang, Yingyang Zhang, Hao Dong, Xiaoguang Zhang, Meihui Wang
Journal of System Simulation
Abstract: In current research on lane detection, existing algorithms can efficiently detect lane lines under good lighting conditions. However, lane detection in low light still faces the challenge of a high false negative rate. A detection algorithm called Instance Association Net(IANet) is proposed to address this issue by utilizing the structural relationships between lane lines, which is helpful for low light conditions. The algorithm first generates unique masks for different lane lines using features at the starting points of the lane lines and a global feature map, achieving instance-level feature separation of the lane lines. It employs an instance-level attention …
Anylogic-Based Platform-Enterprise Collaborative Scheduling Simulation System For Cloud Manufacturing,
2025
School of Mechano-Electronic Engineering, Xidian University, Xi'an 710071, China; State Key Laboratory of Electromechanical Integrated Manufacturing of High-performance Electronic Equipments, Xidian University, Xi'an 710071, China
Anylogic-Based Platform-Enterprise Collaborative Scheduling Simulation System For Cloud Manufacturing, Linxuan Wang, Yongkui Liu, Lin Zhang, Tingyu Lin, Lihui Wang
Journal of System Simulation
Abstract: Aiming at the lack of research on collaborative scheduling between a cloud manufacturing platform and associated enterprises, as well as the lack of simulation systems to simulate scheduling strategy combinations and to visualize dynamic scheduling processes, a simulation system that supports visualization of cloud manufacturing platform-enterprise collaborative dynamic scheduling processes is designed and developed. System requirements are analyzed in detail, and then a scalable platform-enterprise collaborative scheduling model and system functional architecture based on hierarchical multi-agents is proposed. Combined with a case of supply chain of industrial robots, considering random selection, time optimal strategy in the cloud manufacturing …
Digital Twin Modeling Method For Bulk Cargo Stacks Based On 2d Lidar,
2025
School of Logistics Engineering, Shanghai Maritime University, Shanghai 201306, China
Digital Twin Modeling Method For Bulk Cargo Stacks Based On 2d Lidar, Houjun Lu, Yifei Zhu, Yanping Rong, Wanghui Zhang
Journal of System Simulation
Abstract: Due to the characteristics of large equipment, harsh working environment and time-varying shape of the material pile in bulk cargo terminal, there are some disadvantages such as low data accuracy and poor stability when building the storage yard model, which affects the unmanned and intelligent operation control. In this paper, we use two-dimensional laser radar combined with equipment mechanism motion to scan material pile point cloud data, present a digital twin modeling method for bulk storage yard, which includes static scene construction of storage yard and real-time modeling of material pile. Prefabricated models are used for the static scenes …
Research On Strong Real-Time Synchronisation Algorithm For Lvc Co-Simulation,
2025
School of Software Engineering, South China University of Technology, Guangzhou 510006, China
Research On Strong Real-Time Synchronisation Algorithm For Lvc Co-Simulation, Junhui Li, Songtao Sun, Fei Liu
Journal of System Simulation
Abstract: Live, virtual, and constructive(LVC) joint simulation has become a hot research topic of current military simulation; however, existing time management strategies usually fail to meet the needs of strict real-time performance of LVC. A LVC joint simulation synchronization algorithm is proposed that starts with a window sliding-based median smoothing strategy and real time drift rate-based clock compensation strategy for effective node synchronization. A novel hybrid timing strategy is introduced combining long and short cycles implemented in software, which balances precision and efficiency. A simulation catch-up strategy is proposed to address software delays, which combined with the highprecision timing strategy, …
Digital Imaging Simulation Of Complex Scene Of Space-Based Space Small Target,
2025
Changchun Institute of Optics, Fine Mechanics and Physice, Chinese Academy of Sciences, Changchun 130033, China; University of Chinese Academy of Sciences, Beijing 100039, China; Key Laboratory of Space-Based Dynamic & Rapid Optical Imaging Technology, Chinese Academy of Sciences, Changchun 130033, China
Digital Imaging Simulation Of Complex Scene Of Space-Based Space Small Target, Pengfei Li, Wei Xu, Yongjie Piao, Yinghong Fang, Dunpan Shi
Journal of System Simulation
Abstract: In response to the universal demand for space target detection technology research in space image data sources, this study focuses on the problems of insufficient training data for intelligent algorithms and the use of single data for traditional algorithms, with the goal of generating dynamic digital sequence images of small space targets in complex scenes. A visible light digital imaging simulation system based on a space observation platform is designed. A small target imaging model is proposed, which is based on two-dimensional shape feature point description and imaging analysis model to carry out digital modeling and imaging simulation of …
Control Strategy For Uav Cluster Formation Rendezvous Based On Lde-Maddpg Algorithm,
2025
Joint Logistic Support Force Engineering University of PLA, Chongqing 401311, China
Control Strategy For Uav Cluster Formation Rendezvous Based On Lde-Maddpg Algorithm, Wei Xiao, Jiabo Gao, Xueliang Ke
Journal of System Simulation
Abstract: To solve the problem of difficulty in UAV cluster formation rendezvous based on MADDPG algorithm, an autonomous collaborative control strategy based on LDE-MADDPG algorithm is proposed. To address the issues of weak generalization, poor scalability, and slow cluster training process of MADDPG algorithm, LDE-MADDPG algorithm was proposed by designing a state feature learning network and a decoupled Critical network. By integrating LDE-MADDPG algorithm with strategy generation elements such as the decoupled reward function, cluster state space, and UAV action space, a control strategy for UAV cluster formation endezvous that can adapt to diverse formations and varying quantities has been …
Robot Path Planning Based On Improved A-Ddqn Algorithm,
2025
School of Mechanical and Electrical Engineering, Henan University of Science and Technology, Luoyang 471003, China
Robot Path Planning Based On Improved A-Ddqn Algorithm, Peilong Ni, Pengjun Mao, Ning Wang, Mengjie Yang
Journal of System Simulation
Abstract: An improved A-DDQN algorithm is proposed to address the challenges of reward sparsity and the inability to distinguish sample importance in traditional DQN algorithms during robot path planning. Building on the original DQN, an enhancement is made by incorporating the Double-DQN approach, which updates the predictive Q-value network based on actions selected by the Q network, rather than directly using the predicted Q-values for action selection, thereby mitigating overestimation issues. Secondly, the concept of artificial potential field (APF) is introduced to design specific rewards for each step of the robot's movement, guiding the robot and addressing the problem of …
Design And Development Of A Standalone Digital Holographic Microscope Employing Phase-Driven Reconstruction And Classification For Biomedical Imaging And Optical Diagnostics,
2025
University of Massachusetts Boston
Design And Development Of A Standalone Digital Holographic Microscope Employing Phase-Driven Reconstruction And Classification For Biomedical Imaging And Optical Diagnostics, Charlotte Kyeremah
Graduate Doctoral Dissertations
Access to advanced biomedical imaging technologies remains a significant challenge in resource-limited settings, especially for early disease detection and monitoring of diseases such as malaria, HIV, and other blood-borne diseases. Although point-of-care (POC) devices have gained popularity in global health, many rely on antibody-based tests, lateral flow strips, or optical readouts that often lack quantitative capabilities, sensitivity to early infections, or versatility in different diagnostic targets. In addition, these systems are typically dependent on disposable reagents or manual interpretation, which limits their effectiveness in remote areas. Digital Holographic Microscopy (DHM) presents a promising alternative as a label-free imaging method capable …
Simulating Chemiluminescence Spectra Of Oh Radical Using Quantum Dynamical Simulations,
2025
University of Dayton
Simulating Chemiluminescence Spectra Of Oh Radical Using Quantum Dynamical Simulations, Triet M. Cao
Research from the Berry Summer Thesis Institute, 2025
Chemiluminescence is a phenomenon of light emission that occurs when molecules transition from an excited state to the ground state. This phenomenon is widely utilized in applications ranging from quantifying product yields in chemical reactions to biological imaging and atmospheric chemistry studies. It has also been used in many crucial applications in the scarce conditions of heat and electricity, such as light sources for astronomy discovery or deep-sea diving. A notable example of such reactions is combustion, where highly reactive hydroxyl radicals (OH) are products. These radicals exhibit a chemiluminescence spectrum because of the interaction between their ground state and …
Mapping The Research Landscape Of Covid-19 And Artificial Intelligence Using The Lens Database,
2025
Effat University
Mapping The Research Landscape Of Covid-19 And Artificial Intelligence Using The Lens Database, Aichetou Mohamed Sidiya, Jailan Fouad Aljizawi
Effat Undergraduate Research Journal
Due to the rapid spread of the COVID-19 pandemic, all countries faced a significant challenge in their efforts to monitor and halt the spread of the virus. Moreover, researchers around the world raced into publishing to get to understand the effects of this pandemic on every aspect of our life whether that was economic, medical, or social. Thus, this research seeks to assess the quality of research on the application of Artificial Intelligence in the Covid-19 pandemic with an emphasis on Saudi Arabia. The research methodology is based on Bibliometric Analysis techniques and VosViewer for various bibliometric visualizations based on …
Designing A Data Collection And Visualization Toolkit For Scalable Tensor Algebra In Quantum Chemistry Applications,
2025
Louisiana State University and Agricultural and Mechanical College
Designing A Data Collection And Visualization Toolkit For Scalable Tensor Algebra In Quantum Chemistry Applications, Epiya J. Ebiapia
LSU Master's Theses
Large-scale quantum chemistry computations, such as those executed with the Tensor Algebra for Many-body Methods (TAMM) framework, require careful configuration of runtime parameters to achieve high performance and cost efficiency in high-performance computing (HPC) and cloud environments. Without effective performance analysis tools, researchers risk inefficient use of computational resources, leading to longer runtimes and higher costs.
To address this challenge, this thesis presents the design and implementation of a performance profiling and visualization toolkit for TAMM, developed as part of the DOE TEC4 project in collaboration with Pacific Northwest National Laboratory, Microsoft, and Louisiana State University. The toolkit collects detailed …
Detection Of Small Apple Targets Based On Improved Yolov5 In Natural Environments,
2025
School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China
Detection Of Small Apple Targets Based On Improved Yolov5 In Natural Environments, Zilong Liu, Lei Zhang
Journal of System Simulation
Abstract: The distribution of apples usually features occlusion and small and dense targets. To address these issues, a target detection algorithm was proposed based on an improved YOLOv5 model. Specifically, this paper added the coordinate attention (CA) mechanism, receptive field block (RFB), and adaptively spatial feature fusion (ASFF) modules to the YOLOv5, enhancing the ability to detect small targets. Additionally, the proposed algorithm replaced the CIoU in YOLOv5 with SIoU to improve the target detection box's prediction accuracy. Finally, some normal convolutions were replaced with depthwise separable convolutions (DSC), effectively reducing the calculation burden. Experiment results show that the comprehensive …
Scene Generation Method For Maritime Target Recognition Based On Detection Parameters,
2025
National Key Laboratory of Reliability and Environmental Engineering, Beijing 100191, China; School of Reliability and Systems Engineering,
Beihang University, Beijing 100191, China
Scene Generation Method For Maritime Target Recognition Based On Detection Parameters, Yuxuan Run, Dezhen Yang, Yeyang Liu, Wei Deng, Xiangyu Xing, Yi Ren
Journal of System Simulation
Abstract: Traditional scene generation methods for maritime target recognition consider only the effects of different environments on the generated scene data, while overlooking the changes in scene information caused by sensor detection parameters, resulting in a lack of accuracy and authenticity in generated scenes. To address this issue, a detection parameter-based scene generation method for maritime target recognition was proposed. For the task of maritime target recognition, key detection parameters affecting scene generation quality and essential scene features were analyzed. An association relationship modeling method based on Bayesian networks was proposed to construct a mapping relationship model between scene features …
Ship Fire Prediction Method Based On Evidence Theory With Fuzzy Reward,
2025
Navigation College, Dalian Maritime University, Dalian 116026, China
Ship Fire Prediction Method Based On Evidence Theory With Fuzzy Reward, Chunyu Yang, Chuang Zhang, Xiaofan Zhang
Journal of System Simulation
Abstract: A multi-source information fusion approach based on the dempster-shafer (D-S) evidence theory with a fuzzy reward-penalty mechanism was proposed to address the issues of underreporting and false reporting in the early prediction of ship fires. PyroSim was utilized to construct a ship's laboratory model for fire simulation. Variations in carbon monoxide, temperature, and smoke concentration were recorded for data acquisition, followed by the application of a sigmf function for membership assignment. By leveraging the classical D-S theory, a reward-penalty mechanism was applied in weighted evidence fusion. Reward-penalty factors were utilized to differentiate various basic probability assignments, with unified belief …
Research On Joint Simulation Of Special Vehicle Engine Operation Characteristics Based On Virtual Driving Scenarios,
2025
School of Mechanical Engineering, Beijing Institute of Technology, Beijing 100080, China
Research On Joint Simulation Of Special Vehicle Engine Operation Characteristics Based On Virtual Driving Scenarios, Xueyuan Xie, Chen Lin, Han Wu, Qinglan Zhao, Junfei Gao, Qiangguo Hao, Xinqian Zheng
Journal of System Simulation
Abstract: The preliminary design of the overall operation performance of diesel engines cannot be guided by actual vehicle driving tests, which hinders the improvement of the power development level and efficiency of special vehicles. By using the virtual visual simulation engine Unity3D, two virtual driving scenario models were established: a flat road scenario and an undulating road scenario. Based on the speed characteristic parameters of the engine, a diesel engine's operation performance output model was constructed. Combined with the transmission system model and the longitudinal dynamics model of the vehicle's center of mass, a straight vehicle driving dynamics model was …
Simulation And Optimization Of Support Processes For Aircraft Fleet Launch Under Limited Resources,
2025
University of Electronic Science and Technology of China, Chengdu 611731, China; AVIC Chengdu Aircraft Design & Research Institute, Chengdu 610031, China
Simulation And Optimization Of Support Processes For Aircraft Fleet Launch Under Limited Resources, Feng Gong, Tao Jiang, Qin Zhang, Yu Liu
Journal of System Simulation
Abstract: To address the scheduling problem of aircraft fleet support processes under limited resources, a fleet support process optimization model that covered multiple aircraft, activities, and resource constraints was developed. An activity node graph model was used to establish the temporal logic, resource competition, and other constraints in the fleet support process, forming a "time – activity – resource" multidimensional optimization model. A genetic algorithm based on priority encoding was proposed, incorporating a serial decoding strategy and a dynamic penalty function to handle the complex constraints in the model, efficiently solving the optimization problem under complicated temporal and resource constraints. …
Short-Term Load Forecasting Based On Dual-Attention Temporal Convolutional Long Short-Term Memory Network,
2025
Department of Computer, North China Electric Power University, Baoding 071000, China; 2. Department of Electronic & Communication Engineering, North China Electric Power University, Baoding 071000, China; Hebei Key Laboratory of Knowledge Computing for Energy & Power, Baoding 071000, China
Short-Term Load Forecasting Based On Dual-Attention Temporal Convolutional Long Short-Term Memory Network, Lifen Li, Jinyue Zhang, Wangbin Cao, Huawei Mei
Journal of System Simulation
Abstract: In order to improve the accuracy of load forecasting and fully extract the hidden relationships between load and other characteristic factors, a load forecasting method based on dual-attention temporal convolutional LSTM network (DA-TCLSNet) was proposed. Correlation analysis was conducted on the dataset using the maximum information coefficient method to perform feature screening to reduce the computational cost of the model. The model input was constructed using a sliding window. The DATCLSNet forecasting model was constructed. The temporal convolutional layer extracted dependencies at different time scales and captured the nonlinear characteristics among variables such as load and weather. The multi-head …
Research On 3d Visualization Of Safety Monitoring And Early Warning For Steel Continuous Casting Scenarios,
2025
School of Civil and Hydraulic Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
Research On 3d Visualization Of Safety Monitoring And Early Warning For Steel Continuous Casting Scenarios, Wei Zhang, Wei Sheng, Yidan Cao, Tingsheng Zhao
Journal of System Simulation
Abstract: In order to improve the visualization and integration of production safety monitoring and fault warning, a three-dimensional (3D) visualization model architecture for whole-process industrial production safety monitoring and early warning for steel continuous casting scenarios was designed. By using 3ds Max and Unity3D, a multi-dimensional and multi-scale model was built, and functional modules such as visualization display and multi-level early warning for safety monitoring data were developed. By combining WebGL technology and Node. js runtime environment, the visualization of whole-process industrial production safety monitoring based on Web terminal was realized. The alarm threshold determination method for whole-process industrial production …
Optimal Scheduling Of An Integrated Energy System Considering Demand Response And Two-Stage P2g,
2025
Department of Automation, North China Electric Power University, Baoding 071003, China; Baoding Sinosimu Technology Co. , Ltd. , Baoding 071051, China
Optimal Scheduling Of An Integrated Energy System Considering Demand Response And Two-Stage P2g, Xinhui Duan, Zelong Cheng, Dongchao Zhang, Xiaochong Duan
Journal of System Simulation
Abstract: In the context of carbon peaking and carbon neutrality goals, this study aims to improve the energy utilization rate and further explore the role of user-side flexible loads and P2G equipment in energy saving and emission reduction. An optimal scheduling model for integrated energy systems considering demand response and two-stage P2G was proposed. A regional integrated energy system coupled with electricity, heating, cooling, gas, storage, and hydrogen was taken as the research object. Models for system equipment and two-stage P2G were established. Based on load characteristics, a multi-load demand response model for electricity, heating, and cooling was constructed using …
