Cooperative Guidance For Multigroup Flight Vehicles Against Multiple Targets With Separated Impact Time,
2025
School of Astronautics, Northwestern Polytechnical University, Xi'an 710072 China
Cooperative Guidance For Multigroup Flight Vehicles Against Multiple Targets With Separated Impact Time, Guofei Li, Shituo Li, Yilun Huangfu, Yueyang Hua, Yunjie Wu, Zongyu Zuo
Journal of System Simulation
Abstract: To cope with cooperative guidance against multiple targets, a distributed cooperative guidance for multigroup flight vehicles to strike multiple targets with separated impact time is proposed. The collaborative variables for multigroup flight vehicles with separated impact time are given, and the guidance law in the line of sight (LOS) is proposed. The guidance laws on the normal and lateral directions of the LOS are proposed to make the LOS deflection angle rate and LOS the inclination angle rate converge rapidly, which ensures that each vehicle is able to strike the target. The finite-time convergence of the proposed guidance laws …
Dynamic Path Planning For Robotic Arms Based On An Improved Ppo Algorithm,
2025
School of Mechano-Electronic Engineering, Xidian University, Xi'an 710071, China
Dynamic Path Planning For Robotic Arms Based On An Improved Ppo Algorithm, Yuhang Wan, Zilu Zhu, Chunfu Zhong, Yongkui Liu, Tingyu Lin, Lin Zhang
Journal of System Simulation
Abstract: Aiming at the increased environmental uncertainties and more difficult modeling for robotic arm path planning in unstructured environments, an approach to dynamic path planning of robotic arms based on an improved PPO algorithm is proposed. In order to solve the problem that the input length of the state space is not fixed due to the change of number of obstacles in dynamic environment, an environmental state input processing method based on the LSTM network is proposed, and the network structure of PPO algorithm is also improved; a reward function is designed based on the artificial potential field method, and …
Aerial Target Detection Algorithm Fused With Multi-Scale Features,
2025
School of Communications and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
Aerial Target Detection Algorithm Fused With Multi-Scale Features, Lu Yang, Junying Pei
Journal of System Simulation
Abstract: In order to solve the problem that UAV aerial images have a large number of small target samples but little extractable feature information, which is not conducive to improving the accuracy of aerial target detection, an improved small target detection algorithm for aerial photography based on YOLOv8s is proposed. The algorithm applies deformable convolution to the feature extraction module of the backbone network to adaptively capture the details of the target at different locations and scales. The feature information at different scales of the backbone network is extracted and enhanced by the feature collection module in the multilevel information …
Operation System For Simulation Roadheader Based On Visual Motion Capture,
2025
School of Mechanical and Electrical Engineering, Anhui Jianzhu University, Hefei 236001, China; Key Laboratory of Intelligent Manufacturing of Construction Machinery, Anhui Education Department, Hefei 230601, China; Sichuan Provincial Key Laboratory of Process Equipment and Control Engineering, Zigong 643000, China
Operation System For Simulation Roadheader Based On Visual Motion Capture, Yongling Li, Lingzhi Liu, Baishun Zhou, Jingfa Lei, Miao Zhang, Ruhai Zhao
Journal of System Simulation
Abstract: To enhance the natural human-machine interaction in simulation roadheader environment, a vision-based simulation roadheader operation system is proposed. The visual motion capture unit is based on the MediaPipe framework, which captures hand gestures through cameras and creates a correspondence between the physical world and virtual space. An improved Kalman filter algorithm is proposed by setting a weighted centroid to address the issue of unreasonable jumps in hand keypoint data during large-scale movements. The operator's gestures are discerned and the corresponding commands are conveyed. The results show that the improved method has significant advantages over the control group in terms …
Research On Behavior Control Techniques For Autonomous Vehicles Based On Parallel Behavior Tree Architecture,
2025
College of Systems Engineering, National University of Defense Technology, Changsha 410073, China
Research On Behavior Control Techniques For Autonomous Vehicles Based On Parallel Behavior Tree Architecture, Jianchao Yuan, Shuo Yang, Qi Zhang, Ge Li
Journal of System Simulation
Abstract: Aiming at the problem of high collision rate and low efficiency of traditional serial behavior tree in autonomous vehicle control, a solution based on improved parallel behavior tree architecture is discussed to achieve safe behavior control. A safety behavior control strategy under dynamic road conditions is proposed, and behavior models for observation, decision-making, and movement are constructed, as well as their temporal constraint relationships; an improved parallel behavior tree control architecture is proposed, which achieves parallel execution and real-time interaction of behaviors through parallel control nodes, improving the real-time performance of decision control. The results show that compared with …
Research On Improving Design Efficiency Of Coaxial Magnetic Gear Based On Linear Model,
2025
AECC Beijing Institute of Aeronautical Materials, Beijing 100095, China
Research On Improving Design Efficiency Of Coaxial Magnetic Gear Based On Linear Model, Shuguang Zhao, Ce Chen, Xiaochang Xie, Fuping Li, Jin Han
Journal of System Simulation
Abstract: To address the issues of large model computation load and cumbersome magnetization direction setting during the simulation design of coaxial magnetic field modulation type magnetic gears, a simplified design method is proposed, which uses a linear model to replace the original conventional circular ring model. Based on the periodicity of the structure and magnetic field of each part of the magnetic gear, the modeling work is simplified and the computational load of the simulation analysis is reduced. The results show that compared with the circular ring structure, the number of magnetization coordinate system settings for the linear structure is …
How’S It Growing? Tools For Observing Snow And Sea Ice In A Changing Arctic Ocean,
2025
Thayer School of Engineering at Dartmouth College
How’S It Growing? Tools For Observing Snow And Sea Ice In A Changing Arctic Ocean, Ian Alexander Raphael
Dartmouth College Ph.D Dissertations
September Arctic sea ice extent has diminished by roughly 50% in the 45 years since satellite observations began. The Arctic Ocean may experience ice-free summers within the next decade, with implications for habitat, resource extraction, geopolitics, and local and global climate change. To predict how Arctic sea ice will change in the future, we need to understand its behavior in the present. In situ sea ice mass balance measurements (snow accumulation, ice growth, snow and ice surface melt, and bottom melt) are essential for studying the processes driving rapid changes in the ice pack, and for validating remote sensing measurements …
Enhancing Multi-Step Stock Price Forecasting With Social Media Sentiment And Engagement Metrics,
2025
University of Denver
Enhancing Multi-Step Stock Price Forecasting With Social Media Sentiment And Engagement Metrics, Damilare Olaniyan
Electronic Theses and Dissertations
This thesis investigates whether social media sentiment can improve the accuracy of stock price prediction beyond traditional historical data. While financial markets have long relied on structured numerical indicators, the growing influence of public discourse on platforms like Twitter has introduced new opportunities for extracting market-relevant signals from unstructured text. The study focuses on four major technology firms and combines sentiment features derived from Twitter with historical stock prices in a hybrid machine learning framework. Engagement-weighted sentiment, linguistic complexity, and polarity intensity were extracted using natural language processing techniques and incorporated into classification and regression models. Results show that including …
A Comparative Study Of Neural Networks And Xgboost Models For Flight Time Prediction,
2025
Embry-Riddle Aeronautical University, Daytona Beach
A Comparative Study Of Neural Networks And Xgboost Models For Flight Time Prediction, Ioannis Paraschos, Taryn E. Trimble, Eshna Bhargava, Jake Klingler, Benjamin R. Nicolai
Beyond: Undergraduate Research Journal
Flight time prediction plays a crucial role in modern air travel, benefiting airlines and passengers alike. Accurate predictions enable airlines to optimize schedules, allocate resources effectively, and ensure passenger safety and satisfaction. In recent years, machine learning models, such as neural networks and XGBoost, have gained popularity for predicting flight times. This study aims to compare the performance of neural network and XGBoost models in predicting flight times, considering factors such as weather conditions, air traffic control, and aircraft performance. The results indicate that both models are effective, with XGBoost achieving slightly higher accuracy. However, neural networks offer advantages in …
Filling Gaps In Scientific Data Sets Using Physics Informed Neural Networks: A Case Study In Velocity Fields,
2025
California Polytechnic State University, San Luis Obispo
Filling Gaps In Scientific Data Sets Using Physics Informed Neural Networks: A Case Study In Velocity Fields, Ellen Saunders
Master's Theses
Gaps in scientific data sets are a persistent issue for researchers in a variety of fields, and while nothing makes up for missing out on real data, well-simulated synthetic data can be a useful tool. In the world of image processing, machine learning techniques have become quite sophisticated at taking an image with a missing component and filling in that space with something believable. The aim of this thesis is to take machine learning techniques similar to what gets used in image processing and repurpose them to infill gaps in scientific data sets in a realistic manner. This thesis compares …
On The Design Of A Framework For Large-Scale Exploratory Graph Analytics,
2025
New Jersey Institute of Technology
On The Design Of A Framework For Large-Scale Exploratory Graph Analytics, Oliver Andres Alvarado Rodriguez
Dissertations
Large-scale exploratory graph analytics merges data science with high-performance computing to extract critical insights from network-representable data. Data scientists routinely analyze data from the natural, social, and computing sciences by representing it as networks, or graphs, where objects become vertices and their relationships become edges. This representation allows data scientists to add graph analytics to their toolbox. However, designing tools for large-scale exploratory graph analytics is challenging due to the complexities of graph algorithms, such as high communication in distributed systems and large memory demands. These challenges can lead to overly complex software, which limits usability and development to a …
Research On Grey-Box Modeling Method Of Digital Twins For Cantilever Structure,
2025
Department of Automation, Tsinghua University, Beijing 100084, China
Research On Grey-Box Modeling Method Of Digital Twins For Cantilever Structure, Wenjia Zhang, Heming Zhang
Journal of System Simulation
Abstract: The construction of accurate and highly real-time digital twin models in complex industrial setting presents several challenges. Traditional model construction approaches based only on mechanism or data show certain limitations. Therefore, this study is based on the idea of grey-box modeling, taking the cantilever structure within a boom-type roadheader as the object, and proposes a novel modeling approach that combines the characteristics of the mechanism model and introduces a self-attention mechanism. This method performs grayscale transformation on the original input and splices it with physical features to achieve organic fusion of mechanism information, which not only enhances the expressiveness …
An Extended Image Features Based Uncalibrated Visual Servoing Method,
2025
School of Electrical and Mechanical Engineering, Lanzhou University of Technology, Lanzhou 730050, China
An Extended Image Features Based Uncalibrated Visual Servoing Method, Shuzhen Zhang, Yukun Cheng, Yangbo Liu, Fusheng Zha
Journal of System Simulation
Abstract: Aiming at the traditional uncalibrated visual servo relying on the estimation of image Jacobi matrix and the coupling of the motion of each degree of freedom of the camera, on the basis of imagebased uncalibrated visual servo, an extended image features based uncalibrated visual servo method is proposed. By analyzing the relationship between image features and camera frames change in the visual servoing process, the visual servoing process in the image space is decomposed into four basic processes: translation, stretching, rotation and scaling; by analyzing the changing of image features in the visual servoing process, extended image features are …
A Modeling And Simulation Method For Firepower Intelligent Decision-Making Of Directed Energy System Basedon Joint Dqn,
2025
China Jiuyuan Hi-tech Equipment Corporation Limited, Beijing 100094, China
A Modeling And Simulation Method For Firepower Intelligent Decision-Making Of Directed Energy System Basedon Joint Dqn, Changhong Qu, Junjie Wang, Kun Wang, Qingyong Cui, Jiangyang Chen, Xinpeng Wang
Journal of System Simulation
Abstract: In order to solve the problem of dynamically addressing firepower intelligent decision-making in anti-UAV cluster combat using a directed energy system, a deep reinforcement learning model is established. Based on the high multi-agent state and action space dimensions of this model, a modeling and simulation method of firepower intelligent decision-making of directed energy system based on joint deep Q network (DQN) is proposed. The state space is constructed from the state of directed energy system, UAV cluster and the directed energy system deployment area. The joint mechanism is used to share the state information of each equipment and the …
Adaptive Multi-Scale Feature Pyramid Network For Occlusion Pedestrian Detection,
2025
School of computer science and Engineering Anhui University of Science and Technology, Huainan 232001, China; School of Economics and management, Anhui University of Science and Technology, Huainan 232001, China
Adaptive Multi-Scale Feature Pyramid Network For Occlusion Pedestrian Detection, Huaping Zhou, Tao Wu, Kelei Sun
Journal of System Simulation
Abstract: To address the issue of current pedestrian detectors, which struggle to extract complete features in occlusion-heavy environments and consequently have low detection accuracy. A novel adaptive multiscale feature pyramid network is proposed. A multi-scale feature enhancement module (MFEM) is developed. It captures the visible area of pedestrians at different scales through a multi-branch network with different receptive fields. An AFM (adaptive fusion module) is proposed. It calculates the importance of different pixels by optimizing the mean variance at the spatial and feature levels. It enhances the texture and semantic features of pedestrians and fuses the features of different scales …
Modeling And Simulation Of Intelligent Underwater Acoustic Countermeasure Based On The Matrix Game,
2025
School of Science, Wuhan University of Technology, Wuhan 430070, China
Modeling And Simulation Of Intelligent Underwater Acoustic Countermeasure Based On The Matrix Game, Huijin Zhao, Yu Chen
Journal of System Simulation
Abstract: Due to the great threat of torpedo against surface warships, an efficient hydroacoustic countermeasure system must output real-time strategies to accommodate varied antagonizing scenarios. Aiming at the decision-making problem in the anti-torpedo hydroacoustic countermeasure cases, an intelligent adversarial strategy is proposed based on the game theory. By discretizing the strategy space of both sides, a matrix game model is established where the payoff is characterised by the capture probability of attacking torpedo. An improved simplex algorithm is then developed to get the mixedstrategy Nash equilibrium of the game model, which can be used to obtain preferred avoidance strategies to …
Optimal Scheduling Of Virtual Power Plant With Coupled Operation Of Ccs-P2g Considering Wind And Photovoltaic Uncertainty,
2025
Marketing Service Center of State Grid Ningxia Electric Power Co. , Ltd. , Yinchuan 750001, China
Optimal Scheduling Of Virtual Power Plant With Coupled Operation Of Ccs-P2g Considering Wind And Photovoltaic Uncertainty, Xurong Jin, Jiang Yin, Guohua Yang, Wei Li, Guobin Wang, Lele Wang, Na Yang, Xuenian Zhou
Journal of System Simulation
Abstract: In order to solve the problem that the uncertainty of wind power and photovoltaic power generation output easily affects the scheduling of virtual power plant, a new optimal scheduling model of virtual power plant is proposed based on information gap decision theory (IGDT) . In order to reduce the carbon emission of the system, carbon capture and storage (CCS) is installed on the combined heat and power units; in order to improve the utilization rate of renewable energy, the power to gas (P2G) device is introduced into the system, and the operation mode of CCS-P2G coupling is proposed; based …
A Quadrotor Trajectory Tracking Control Method Based On Deep Reinforcement Learning,
2025
School of Automation Central South University, Changsha 410083, China
A Quadrotor Trajectory Tracking Control Method Based On Deep Reinforcement Learning, Guohua Wu, Jiaheng Zeng, Dezhi Wang, Long Zheng, Wei Zou
Journal of System Simulation
Abstract: Traditional quadrotor controllers, constrained by fixed model equation structures, encounter challenges in addressing control errors stemming from variations in parameters and environmental disturbances. This paper proposes a deep reinforcement learning solution for the quadrotor trajectory following control problem. We present the PPO-SAG algorithm incorporated into the PPO framework, utilizing adaptive mechanisms and PID expert knowledge to enhance training convergence and stability. Target functions incorporating distance constraint penalties and entropy policies are designed in alignment with the characteristics of the given problem. We also devise innovative disturbance-adaptive structures and trajectory feature selection mechanisms to augment control error information and extract …
Optimization Of Cargo Location Allocation In Four-Way Shuttle Warehousing System Based On Two-Stage Hybrid Algorithm,
2025
Institute of Logistics Science & Engineering, Shanghai Maritime University, Shanghai 201306, China
Optimization Of Cargo Location Allocation In Four-Way Shuttle Warehousing System Based On Two-Stage Hybrid Algorithm, Zisong Wu, Daofang Chang, Yuchun Gai
Journal of System Simulation
Abstract: To address issues such as the dense distribution of storage locations and the potential congestion of shuttle vehicles in the four-way shuttle dense storage system, a grid-based approach to the storage location distribution is developed. A location allocation model is then constructed with the goals of ensuring shelf stability, improving warehousing efficiency, and balancing equipment utilization. A twostage hybrid algorithm is designed for the model. In the first stage, the local search strategy of nondominant sequencing genetic algorithm(NSGA-II) is enhanced by incorporating the hill climbing algorithm to address a set of Pareto front sets. In the second stage, the …
Research On A Credibility Information Management Method Of Simulation Modeling,
2025
School of Cyberspace Security, Northwestern Polytechnical University, Xi'an 710072, China
Research On A Credibility Information Management Method Of Simulation Modeling, Qiming Gu, Jiazhi Chen, Guoyan Cao, Chenchu Zhou, Dengxiu Yu, Haifeng Hu
Journal of System Simulation
Abstract: A proposed method for managing credibility information in simulation modeling draws insights from the NASA-STD-7009 standard for modeling and simulation. From the perspective of credibility information recording, definition, and assessment, this method aims to address the core issue of whether the credibility requirements are met in simulation modeling research. A simulation system credibility information extraction tool is designed to extract three types of information including modeling credibility information, data credibility information, and development process credibility information, enabling recording, definition, and traceability of credibility information in simulation models. Taking a servo system credibility evaluation as an example, a simulation system …
