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Articles 241 - 270 of 310
Full-Text Articles in Systems Science
Research On Robot Path Planning Based On Improved Harris Hawks Algorithm, Yuxin Bai, Zhenya Chen, Ruitao Shi, Weitao Su, Zhuoqiang Ma, Shangjin Yang
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 …
Research On Air Target Threat Assessment Technology Based On Deep Learning, Dawei Jiang, Yangyang Dong, Lidong Zhang, Xiao Lu, Chunxi Dong
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 …
Design And Verification Of Display And Control System Based On Mbse And Vaps For Civil Helicopter, Xi Cao, Bo Liu, Bingzhi Su, Tao Nie
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 …
Cae Simulation Optimization Method Based On Dynamic Coupling Model, Xue Chen, Jianwen Cao
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 …
Vibration Simulation And Multivariate Statistical Analysis Method Of Composite Structures, Bo Guo, Ming Tie, Wenhui Fan
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 …
An Intelligent Ambulance Regulation Model Based On Online Reinforcement Learning Algorithm, Lei Zhang, Xuechao Zhang, Chao Wang, Xianglei Bo
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 …
City Regional Traffic Flow Prediction Based On Spatiotemporal Multi-View Attention Residual Network, Jing Chen, Guowei Yang, Zhaochong Zhang, Wei Wang
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 …
Tohf: A Feature Extractor For Resource-Constrained Indoor Vslam, Ruoqing Li, Yaochi Zhao, Zhuhua Hu, Wenlu Qi, Guangfeng Liu
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 …
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
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 …
Visual Slam Algorithm Based On Feature Point Selection In Dynamic Scenes, Limei Jiang, Xinwei Chen
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 …
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
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 …
Research On Transformer Fault Diagnosis Method Based On Digital Twin, Lun Jiang, Dajiang Wang, Wenlei Sun, Shenghui Bao, Han Liu, Saike Chang
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; …
Multi-Strategy Hybrid Mountain Gazelle Optimizer For Robot Path Planning, Xu Jin, Yuanbin Mo
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 …
Dynamic Spectral And Systems-Theoretic Approaches For Inference And Control Of Heterogeneous Complex Networks, Bharat Kumar Singhal
Dynamic Spectral And Systems-Theoretic Approaches For Inference And Control Of Heterogeneous Complex Networks, Bharat Kumar Singhal
McKelvey School of Engineering Graduate Student Theses & Dissertations
Networks of nonlinear systems are commonly employed to describe a diverse range of phenomena across physics, engineering, neuroscience, and biology. The undesirable behaviors of such systems, in the form of neurological disorders, power grid failures, or ecological collapses, have spurred significant interest in understanding their dynamic structures and developing effective control strategies. These systems are typically large-scale, consist of heterogeneous units, and are partially observable with limited measurement data, presenting theoretical and computational challenges for control design and connectivity inference. This thesis addresses these challenges by developing novel algorithms for pattern formation in populations of stable limit-cycle oscillators and connectivity …
Analysis Of Systematic Trade-Offs Between Military And Healthcare Expenditure Alongside Gdp Growth Of Select Asian And Western Exporting Economies In The 21st Century, Rahul Balamurugan, Carlos Gershenson, Preethi Nanjundan, Hiroki Sayama
Analysis Of Systematic Trade-Offs Between Military And Healthcare Expenditure Alongside Gdp Growth Of Select Asian And Western Exporting Economies In The 21st Century, Rahul Balamurugan, Carlos Gershenson, Preethi Nanjundan, Hiroki Sayama
Northeast Journal of Complex Systems (NEJCS)
This study explores the complexity in the trade-offs between military expenditure, healthcare expenditure, and GDP growth across select Asian nations and major weapon-exporting countries, examining how nations allocate finite resources between national security and human well-being over the past two decades. Using a systems science approach, the research integrates Granger causality testing to analyze temporal and directional relationships among GDP growth, military expenditure, and healthcare expenditure, uncovering their dynamic interdependencies. The methodology includes trend and slope analysis, Granger causality testing, outlier detection, and clustering to identify heterogeneity in resource allocation strategies. Developed, weapon-exporting nations exhibit complementary trends, with strong causality …
Impact Of Node Failures On Productivity In Multilayer Supply Chain Networks: An Influence Network Analysis In The Indian Electronics Sector, Surendra Orupalli, Hiroki Sayama
Impact Of Node Failures On Productivity In Multilayer Supply Chain Networks: An Influence Network Analysis In The Indian Electronics Sector, Surendra Orupalli, Hiroki Sayama
Northeast Journal of Complex Systems (NEJCS)
Supply chain networks are essential for the delivery of goods and information, but disruptions such as natural disasters or trade embargoes can severely impact them. Resilience of entire networks under different types of disruptions when nodes or edges fail has been extensively studied. However, the extent to which the failure of a particular company affects another company of interest within a network has not been widely explored. To address this, we created a multilayer physical supply chain network of companies in an electronics supply chain concentrated in India. Through systematic node removal simulations, we examined how the productivity of one …
Comparative Evaluation Of Linear Regression, Cross Validation And Regularization Approaches In Multivariate Data Analysis, Ransford Owusu, Felix Yeboah, Francis Effah Boateng
Comparative Evaluation Of Linear Regression, Cross Validation And Regularization Approaches In Multivariate Data Analysis, Ransford Owusu, Felix Yeboah, Francis Effah Boateng
Data Science and Data Mining
This study evaluates linear regression and its enhanced variants incorporating cross-validation and regularization techniques for high-dimensional, multivariate datasets. We address challenges such as multicollinearity and overfitting. Methods including Ridge, LASSO, and Elastic Net are compared against ordinary least squares regression. Empirical analysis using an automobile dataset for fuel efficiency prediction shows that while OLS regression captures basic relationships, its limitations are mitigated through regularization and cross-validation, resulting in improved model interpretability. The findings provide a comprehensive framework for predictive modeling in complex data environments and offer insights into statistical methodology and practical applications in the automobile industry.
Improved Bidirectional A* Quadratic Path Planning Algorithm For Mobile Robots, Jiongyi Li, Qiang Li, Xinwen Zhang, Myo Htet Zin, Yongbin Cai
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 …
Research On Task Planning Methods For Space Robot Assisted Operation, Guoqiang Fang, Haitao Chang, Xing Liu, Zhengxiong Liu, Panfeng Huang
Research On Task Planning Methods For Space Robot Assisted Operation, Guoqiang Fang, Haitao Chang, Xing Liu, Zhengxiong Liu, Panfeng Huang
Journal of System Simulation
Abstract: In view of the difficulties caused by the complicated task process and numerous task constraints during the space robot assisted operation, a task planning method combining fast forward search algorithm and hierarchical network algorithm is proposed, in which the task planning process is divided into task planning and replanning. Based on the fast forward search task planning method of operation cost, the execution sequence of actions with minimum operation cost is obtained. The task adaptive replanning method based on hierarchical network corrects and compensates the problems according to the priority of compensation for the movement, grab and release actions. …
Design And Simulation Analysis Of Guidance Law For Boost Phase Interceptor Missile, Xu Zhang, Peng Zeng, Xu Li, Xuehe Zheng, Jianheng Xue, Chao Wang
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 …
Intelligent Service Migration Towards Mec-Based Iov Systems, Sijin Huang, Jia Wen, Zheyi Chen
Intelligent Service Migration Towards Mec-Based Iov Systems, Sijin Huang, Jia Wen, Zheyi Chen
Journal of System Simulation
Abstract: To address the problem of QoS degradation during the vehicle movement, a novel service migration via convex-optimization-enabled deep reinforcement learning (SeMiR) method is proposed. The optimization problem is decomposed into two sub-problems and solved separately. For the service migration sub-problem, an improved deep reinforcement learning based service migration method is designed to explore the optimal migration policy. For the resource allocation sub-problem, a convex optimization based resource allocation method is developed to derive the optimal resource allocation for each MEC server under the given migration decisions, thereby improving the performance of service migration. Experimental results show that the SeMiR …
Intensity-Based Feature Filtering For Lidar-Based Slam, Weigang Li, Shaofeng Zou, Yongqiang Wang, Chuxiang Yu
Intensity-Based Feature Filtering For Lidar-Based Slam, Weigang Li, Shaofeng Zou, Yongqiang Wang, Chuxiang Yu
Journal of System Simulation
Abstract: In order to solve the problem that an excessive influx of feature points into the point cloud registration phase can potentially lead to diminished algorithmic accuracy and suboptimal mapping outcomes, a novel laser SLAM algorithm predicated on the filtering of feature points through the utilization of intensity information is proposed. The intensity distribution near the feature points in the local map is calculated based on the point cloud intensity information, and each feature point within the local map is attributed an intensity distribution index. Through the application of an intensity threshold, feature points that exhibit substantial variations in intensity …
A Hybrid Heuristic Algorithm For Solving The Green Vrp With Priority Delivery, Huanhuan Cui, Lihe Guan
A Hybrid Heuristic Algorithm For Solving The Green Vrp With Priority Delivery, Huanhuan Cui, Lihe Guan
Journal of System Simulation
Abstract: This paper considers the problem that some customers' goods cannot be mixed in logistics distribution. Based on the traditional green vehicle routing problem with simultaneous pickup and delivery, customers are divided into three types: priority delivery, non-priority only pickup without delivery, and non-priority pickup with delivery. A single objective nonlinear optimization model is established to minimize the total cost. A hybrid heuristic method based on simulated annealing and adaptive large neighborhood search algorithm is designed. An improved saving algorithm is used to construct the initial solution. And 5 kinds of destruction operators and 2 kinds of repair operators are …
Coordinated And Optimal Dispatching For Wind-Photovoltaic-Storage Systems Based On Multi-Strategy Multi-Objective Differential Evolution Algorithm, Xuyang Ren, Xuhui Bu, Yanling Yin, Jinghua Liu
Coordinated And Optimal Dispatching For Wind-Photovoltaic-Storage Systems Based On Multi-Strategy Multi-Objective Differential Evolution Algorithm, Xuyang Ren, Xuhui Bu, Yanling Yin, Jinghua Liu
Journal of System Simulation
Abstract: The introduction of new energy generation units makes the power system structure more and more complex, and the existing economic dispatching methods face many challenges. A coordinated and optimal dispatching for wind-photovoltaic-storage systems is constructed and a constraint handling method is given, a competitive mechanism-based multi-strategy multi-objective differential evolutionary (CMMODE) algorithm is proposed. The CMMODE algorithm utilizes a competitive mechanism to partition the population and constructs multiple differential variance operators based on the partitioning results, thus generating a multi-strategy scheme, employs an elite self-exploration mechanism to make the population have the ability to jump out of the local optimum …
An Algorithm For Cloud-Based Web Service Combination Optimization Through Plant Growth Simulation, Qiang Li, Huawei Qin, Bingqin Qiao, Ruifang Wu
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 …
Research On Rule-Based Energy Management Strategy Of Hybrid Mining Dump Truck, Jiangong Liu, Yuanhui Zhang, Fei Wei, Yiying Wang, Xiaoling Li, Peiqing Liu, Fengmiao Si
Research On Rule-Based Energy Management Strategy Of Hybrid Mining Dump Truck, Jiangong Liu, Yuanhui Zhang, Fei Wei, Yiying Wang, Xiaoling Li, Peiqing Liu, Fengmiao Si
Journal of System Simulation
Abstract: A distributed hybrid powertrain system structure and a rule-based energy management strategy are proposed to address the problems of insufficient power and poor fuel economy in conventional dieselpowered mining dump trucks. By analyzing the operational characteristics of mining dump trucks, a distributed hybrid powertrain system structure and vehicle driving conditions are established, relevant mode-switching rules are formulated. The results demonstrate that the proposed distributed hybrid powertrain system structure enhances the climbing capability of the vehicle by 27% when using the third gear for uphill driving. In addition, the adoption of the rule-based energy management strategy results in an 19% …
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
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 …
Construction Of A Digital Twin-Based Ship Manufacturing Workshop Monitoring System, Tianxiang Hu, Hui Ye, Xiaofei Yang
Construction Of A Digital Twin-Based Ship Manufacturing Workshop Monitoring System, Tianxiang Hu, Hui Ye, Xiaofei Yang
Journal of System Simulation
Abstract: In order to address issues of opacity in production information and difficulties in collecting equipment data in shipbuilding workshops, a digital twin ship manufacturing workshop monitoring system is designed based on the Unity physics platform. The essential steps in building a virtual reality platform are outlined, encompassing the creation of a virtual ship workshop, the development of data transmission methods for multi-source heterogeneous data acquisition, implementation of data-driven methods for achieving virtual-real synchronization, and enhancement of data visualization capabilities. By practically designing a real-time monitoring system for the welding assembly line production process in shipbuilding, the 3D scene reproduction …
Improved Target Detection Algorithm For Aerial Images Based On Yolov5, Yecai Guo, Jingdong Sun, Saha Amitave
Improved Target Detection Algorithm For Aerial Images Based On Yolov5, Yecai Guo, Jingdong Sun, Saha Amitave
Journal of System Simulation
Abstract: In order to improve the existing small target detection methods, which suffer from low detection accuracy, high false detection rate and high leakage rate, the FSD-YOLOv5 algorithm is proposed, which has three improvements based on the YOLOv5 algorithm. The Focal EIoU is used instead of the original CIoU to improve the model convergence speed and regression accuracy. To cope with the deficiencies in CNN architecture, we adopt a new CNN building block called SPD-Conv is adopted. To address the problem of the reduced or lost information of small objects in feature maps caused by downsampling in convolutional neural networks, …
Collaborative Optimization Problem Of Dynamic Pre-Maintenance And Green Scheduling, Yuyan Jiang, Ning Ma, Yan Li, Rumeijiang Gan, Fuyu Wang
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 …