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Articles 271 - 300 of 4159
Full-Text Articles in Systems Science
Research On The Truth, Function And Common Principles Of Simulation, Haohua Xu, Bin Xiao, Yunhao Cui
Research On The Truth, Function And Common Principles Of Simulation, Haohua Xu, Bin Xiao, Yunhao Cui
Journal of System Simulation
Abstract: Simulation applications are becoming increasingly widespread and have a greater impact, while the theoretical foundation of simulation is relatively weak. This article provides a new definition of simulation by analyzing the common activities of simulation, which can include both virtual and real simulation forms; referring to Popper's three worlds theory, this paper discusses the objective authenticity of simulation from a philosophical perspective; From a methodological perspective, this paper elaborates on the methodological characteristics of simulation as an indirect cognitive object, revealing its significance in integrating human-machine intelligence and promoting knowledge evolution. It also discusses the common principles of simulation, …
A Model Combining Self-Attention And Weight Sharing For Human Activity Recognition, Lun Ma, Yue Yang, Daihe Wang, Guisheng Liao, Xing Li
A Model Combining Self-Attention And Weight Sharing For Human Activity Recognition, Lun Ma, Yue Yang, Daihe Wang, Guisheng Liao, Xing Li
Journal of System Simulation
Abstract: With the prevalence of wearable devices, human activity recognition based on wearable sensor data has garnered significant attention. The central issue in this field is how to extract effective behavioral information from raw sensor data to form corresponding feature vectors. Currently, convolutional neural networks and recurrent neural networks have been widely utilized for feature extraction from multisensory data. However, these networks struggle to globally capture the crucial temporal features inherent of human activity over time. To address this, a multi-CNN-BiLSTM-self attention (Multi-CBSA) model based on self-attention and weight sharing has been proposed, taking into consideration the logical correlations among …
Station Layout Optimization Method And Simulation For Non-Cooperative Target In Angle Of Arrival Positioning, Yida Ning, Jiongqi Wang, Juhui Wei, Zhenzu Bai, Zhangming He
Station Layout Optimization Method And Simulation For Non-Cooperative Target In Angle Of Arrival Positioning, Yida Ning, Jiongqi Wang, Juhui Wei, Zhenzu Bai, Zhangming He
Journal of System Simulation
Abstract: In the context of angle of arrival (AOA) positioning system for non-cooperative target tracking and positioning, accurately determining true location of the target poses a significant challenge. Conventional station deployment indicators like geometric dilution of precision (GDOP) fail to provide effective guidance for optimization station layout. To address the issue, this study introduces a novel indicator for station optimization and evaluation based on factors that influence positioning accuracy within an angle measurement system. These factors encompass angular differencing, baseline intersection angles, and the observer-target line distance. Moreover, this indicator encompasses the challenges associated with data conformity in "air to …
Wingtip Docking Control Of Composite Aircraft Based On Adrc Theory, Chunlei Xie, Hongxia Hu, Weibo Han
Wingtip Docking Control Of Composite Aircraft Based On Adrc Theory, Chunlei Xie, Hongxia Hu, Weibo Han
Journal of System Simulation
Abstract: The process of wingtip docking in composite aircraft is challenged by significant unsteady vortex aerodynamic disturbances arising from the close-range coupling of wingtips, thereby posing considerable constraints on docking precision and flight safety. This study endeavors to address the intricate task of airborne wingtip docking control amidst wingtip vortex disturbances through a comprehensive investigation of airborne wingtip docking control technology, grounded in the tenets of active disturbance rejection control (ADRC) theory. Initially, a mathematical model encapsulating the dynamics of three-channel attitude/displacement during the docking operation, incorporating both the wingtip docking mechanism and the wingtip vortex model, is established. …
Solving The Vehicle Routing Problem Based On Deep Reinforcement Learning, Ming Jiang, Tao He
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, Yanji Jiang, Yingyang Zhang, Hao Dong, Xiaoguang Zhang, Meihui Wang
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, Linxuan Wang, Yongkui Liu, Lin Zhang, Tingyu Lin, Lihui Wang
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, Houjun Lu, Yifei Zhu, Yanping Rong, Wanghui Zhang
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, Junhui Li, Songtao Sun, Fei Liu
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, Pengfei Li, Wei Xu, Yongjie Piao, Yinghong Fang, Dunpan Shi
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, Wei Xiao, Jiabo Gao, Xueliang Ke
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, Peilong Ni, Pengjun Mao, Ning Wang, Mengjie Yang
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 …
From Model To Behavior: Methodological Challenges In Using Fuzzy Cognitive Maps To Represent Mental Models, Catherine Elizabeth Moore
From Model To Behavior: Methodological Challenges In Using Fuzzy Cognitive Maps To Represent Mental Models, Catherine Elizabeth Moore
Dissertations and Theses
This dissertation examines the use of Fuzzy cognitive maps (FCMs) as representations of mental models and how these representations connect to individual behavior. Fuzzy cognitive maps (FCMs) are semi-quantitative models that encode cause-and-effect structures as directed graphs. They are frequently used to represent individuals' knowledge structures/mental models and should in theory correlate to actions and decisions of individuals; however, this correlation has yet to be explored in a systematic manner. This dissertation represents the first step in experimental research on the connection between FCMs and individual behavior. It examines two theories of how humans use mental models, one based on …
Data Compression In Additive Manufacturing: Recent Progress And Opportunities, Dongmin Ethan Kang, Wenmeng Tian
Data Compression In Additive Manufacturing: Recent Progress And Opportunities, Dongmin Ethan Kang, Wenmeng Tian
Publications
A crucial aspect of quality control for Additive Manufacturing (AM) processes is the acquisition of diverse data from the entire lifecycle of the product. AM data has grown significantly in terms of diversity and volumes, resulting in diverse data formats of increasing volumes, including time series, images, and point clouds. Large quantities of these data are essential for effective in-situ process monitoring and ex-situ non-destructive evaluation. However, this will result in large manufacturing and inspection datasets that are difficult to manage for users, which will delay the broader adoption of AM for mission critical applications. This motivates the urgent need …
The Utilisation Of The Fourth Industrial Revolution (4ir) Technologies In E-Government Service Delivery: A Systematic Literature Review, Arnet Zitha, Noluntu Mpekoa, Sheethal Tom
The Utilisation Of The Fourth Industrial Revolution (4ir) Technologies In E-Government Service Delivery: A Systematic Literature Review, Arnet Zitha, Noluntu Mpekoa, Sheethal Tom
African Conference on Information Systems and Technology
The integration of Fourth Industrial Revolution (4IR) technologies is transforming e-Government by boosting citizen engagement and enhancing service efficiency. However, gaps still exist in understanding the various applications, impacts, and barriers to adoption. This systematic review synthesises literature from 16 studies published between 2017 and 2025, illustrating how technologies like blockchain, artificial intelligence, big data, Internet of Things, and machine learning are employed and their effects on e-Government service delivery. The review reveals that 4IR technologies continue to play a vital role in e-Government services by addressing security threats, simplifying verification and authentication, building trust, and improving the quality and …
An Envisioned And Efficient Design Of Next Generation Decentralized Iot Bot Detection Model, Ahmed Abdullah Almalki
An Envisioned And Efficient Design Of Next Generation Decentralized Iot Bot Detection Model, Ahmed Abdullah Almalki
Doctoral Dissertations
The Industrial Internet of Things (IIoT) and Internet of Medical Things (IoMT) are revolutionizing critical infrastructures, but their expansion has also introduced severe cybersecurity vulnerabilities. Traditional IoT Bot Detection Systems (IBDS) struggle to scale in environments characterized by high-dimensional, large-scale, and redundant network traffic. These challenges hinder the development of reliable cloud-based intrusion detection systems. The limitations of static and rulebased methods in detecting evolving IoT botnet attacks—such as those launched by Mirai and Gafgyt—underscore the need for intelligent, adaptive approaches. To address this, the present study proposes a machine learning and deep learning-driven IoT Botnet Detection Model, validated through …
Detection Of Small Apple Targets Based On Improved Yolov5 In Natural Environments, Zilong Liu, Lei Zhang
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, Yuxuan Run, Dezhen Yang, Yeyang Liu, Wei Deng, Xiangyu Xing, Yi Ren
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, Chunyu Yang, Chuang Zhang, Xiaofan Zhang
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, Xueyuan Xie, Chen Lin, Han Wu, Qinglan Zhao, Junfei Gao, Qiangguo Hao, Xinqian Zheng
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, Feng Gong, Tao Jiang, Qin Zhang, Yu Liu
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, Lifen Li, Jinyue Zhang, Wangbin Cao, Huawei Mei
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, Wei Zhang, Wei Sheng, Yidan Cao, Tingsheng Zhao
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, Xinhui Duan, Zelong Cheng, Dongchao Zhang, Xiaochong Duan
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 …
Storage Life Assessment Methods For Long-Term Storage Products Based On Multi-Scale Simulation: A Review, Hongmin Li, Xiao Han, Shuo Huang, Shengpeng Zhang, Shuanglong Rong, Hao Li, Cheng Qian
Storage Life Assessment Methods For Long-Term Storage Products Based On Multi-Scale Simulation: A Review, Hongmin Li, Xiao Han, Shuo Huang, Shengpeng Zhang, Shuanglong Rong, Hao Li, Cheng Qian
Journal of System Simulation
Abstract: Traditional experiment-based life assessment methods for long-term storage products suffer from drawbacks such as prolonged duration, high cost, and low prediction accuracy, greatly limiting the effectiveness of storage life assessment in practical applications. With the advancement of digital simulation technology, simulation analysis methods based on the physics of failure (PoF) have emerged as a research hotspot in the field of storage life assessment, as they can accurately characterize product aging behavior. The multi-scale characteristics of long-term storage products and their typical storage failure modes and mechanisms were analyzed. Multi-scale modeling and simulation analysis methods for storage failures of fundamental …
Research On Digital Simulation Method For Cognitive Load Evaluation Of Pilots, Zeng Fan, Mingjun He, Xiangyu Xing
Research On Digital Simulation Method For Cognitive Load Evaluation Of Pilots, Zeng Fan, Mingjun He, Xiangyu Xing
Journal of System Simulation
Abstract: The operator's cognitive load constitutes a critical determinant of task performance. Pilots, as the primary operators of aircraft, must face an overwhelming volume of information during complex missions, which significantly heightens the risk of cognitive overload and operational errors. Evaluating cognitive load during tasks helps reduce human errors and improve system safety by optimizing design schemes. A simulation model was established to dynamically predict the pilots' cognitive load during tasks for multi-task scenarios. Based on the multiple resource theory, a method for quantifying cognitive load in multi-task conditions was established. By considering cognitive capacity, task time constraints, task priority, …
Digital Testing And Evaluation: Current Status, Challenges, And Prospects, Bo Sun, Kai Zheng
Digital Testing And Evaluation: Current Status, Challenges, And Prospects, Bo Sun, Kai Zheng
Journal of System Simulation
Abstract: Digital testing and evaluation (DTE) represents a novel paradigm in the evolution of testing and evaluation methodologies within the digital era. It is achieved through the integration of multiple digital theories and technologies to conduct testing and evaluations in the digital domain. This paper analyzed the characteristics of test objects across different historical periods, reviewed the core features of testing and evaluation techniques in each stage, and unveiled the paradigm shifts within the testing and evaluation technology system. Building upon this foundation, it explored the new demands placed on testing by test objects in the information age, clarifying the …
Dynamic Testing Architecture Of Intelligent Unmanned Systems Based On Parallel Battlefields, Dayong Liu, Zhiming Dong, Qisheng Guo, Wenjun Zhang, Jiancheng Gao
Dynamic Testing Architecture Of Intelligent Unmanned Systems Based On Parallel Battlefields, Dayong Liu, Zhiming Dong, Qisheng Guo, Wenjun Zhang, Jiancheng Gao
Journal of System Simulation
Abstract: To improve the inadequacy of traditional test and identification systems, this paper proposed an overall architecture for dynamic testing across the entire lifecycle based on the concept of parallel battlefield (integration of physical, virtual, and cognitive battlefields), meeting the new requirements for the testing of intelligent unmanned systems. This architecture included high-fidelity mapping between virtual and physical battlefields, red-blue adversarial deductions and model optimization, simulation to reality (Sim2Real), human-machine collaboration, and cloud-end integrated control, as well as multidimensional assessment and confidence analysis. Centered on the principles of "mutual driving between virtual and physical battlefields, dynamic closed-loop, human-machine collaboration, and …
Adaptive Sampling And Ghost Multi-Scale Fusion For Lightweight Weld Defect Detection, Bin Lu, Xuan Yang, Zhenyu Yang, Xiaotian Gao
Adaptive Sampling And Ghost Multi-Scale Fusion For Lightweight Weld Defect Detection, Bin Lu, Xuan Yang, Zhenyu Yang, Xiaotian Gao
Journal of System Simulation
Abstract: To improve the accuracy and speed of welding defect detection and achieve lightweight models, a lightweight weld defect detection network based on YOLOv8, named light adaptive-weight sampling-YOLO (LAW-YOLO), was proposed. A lightweight adaptive weight sampling LAWS module was designed. It constructed an adaptive weight attention feature map by learning the interacting features within the receptive field. An optimized efficient weighted bidirectional feature pyramid network was adopted as the feature extraction backbone in LAW-YOLO. Furthermore, a ghost multi-scale sampling module was designed, and a hybrid attention mechanism was introduced to enhance the detection capability for small-scale defect targets. Experimental results …
Optimization Of Product Oil Distribution With Multiple Trips And Multiple Due Dates Under Dynamic Demand, Yong Xie, Hailong Gao, Yutao Chen, Huanjiang Wang
Optimization Of Product Oil Distribution With Multiple Trips And Multiple Due Dates Under Dynamic Demand, Yong Xie, Hailong Gao, Yutao Chen, Huanjiang Wang
Journal of System Simulation
Abstract: In the case of dynamic demand, considering the order due date, vehicle transportation time window, and other factors, this paper developed an optimization model of periodic product oil distribution with multiple trips and multiple due dates to maximize the distribution revenue. The paper also designed a reinforcement learning-based large neighborhood search algorithm to solve the problem. The initial solution was constructed based on the forward insertion heuristic algorithm. Then, a deep reinforcement learning model for neighborhood operator selection was designed. By fitting the action value function through the double deep Q network, the optimal neighborhood operator was selected, and …