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 …
Research On Modeling, Optimization And Application Of Aeroengine Oil System,
2025
Nanjing University of Aeronautics and Astronautics Civil aviation college, Nanjing 211106, China
Research On Modeling, Optimization And Application Of Aeroengine Oil System, Shijie Huang, Zhensheng Zhang, Jing Cai, Rui Zhang
Journal of System Simulation
Abstract: In response to the high cost and long cycle of using experimental methods for monitoring, diagnosing, and predicting lubricating oil system, a simulation model for oil system is constructed and optimized, and the application of the model in health management of oil system is proposed. Based on the physical characteristics of the components in the oil system, subsystem models for ventilation, oil supply, thermodynamics, and oil return are constructed using a certain engine oil system as an example, and the whole oil system model is constructed and solved iteratively. The model is optimized by combining particle swarm optimization and …
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 …
Design And Realization Of Integrated Energy System Dynamic Stability Simulation And Steady-State Simulation System,
2025
China Electric Power Research Institute, Beijing 100192, China
Design And Realization Of Integrated Energy System Dynamic Stability Simulation And Steady-State Simulation System, Guixiong He, Xiaoqiang Jia, Shufeng Dong, Yonglu Han, Yonghua Chen, Yiming Zheng
Journal of System Simulation
Abstract: Aiming for“carbon peak”and“carbon neutrality”, the energy sector is undergoing significant reform. To address energy flow and planning optimization in integrated energy systems, a comprehensive simulation platform is developed. This platform combines physical and digital simulations with real-world validation and is modular in design, It includes an integrated energy model library, energy flow optimization, modeling management, real-time simulation, and energy monitoring. The platform enhances system safety, stability, and economic efficiency, While also improving planning and energy management. The paper analyzes the platform′s functional and physical architecture, introduces key modules, establishes dynamic and steady-state model libraries, and optimizes energy flow using …
Research On Modeling Methods For Industrial Core Capability Architecture Based On The Dodaf Framework,
2025
Defense Industry Program Evaluation Center of sastind, Beijing 100039, China
Research On Modeling Methods For Industrial Core Capability Architecture Based On The Dodaf Framework, Xiaoqiang Dou, Yan Liu, Zhilong Zhao, Chao Fu, Fulin Zhang, Shanshan Zou
Journal of System Simulation
Abstract: Against the backdrop of the industrial sector actively pursuing digital capability building, this paper describes the necessity and current status of architecture theory methods guiding industrial core capability construction. It proposes the conceptual connotation of industrial core capability architecture and four key modeling elements. Based on DoDAF, it conducts the overall design of industrial core capability architecture. By integrating systems engineering principles, it establishes a five-stage process model for capability-building activities, embedding critical elements such as capability/business/ application/data/technology architecture viewpoint, and explains data model design, and logical compositions of various viewpoints. By selecting a capability building project in a …
Survey On Large Language Agent Technologies For Intelligent Game Theoretic Decision-Making,
2025
College of Intelligence Science and Technology, National University of Defense Technology, Changsha 410073, China
Survey On Large Language Agent Technologies For Intelligent Game Theoretic Decision-Making, Xueqiang Gu, Junren Luo, Yanzhong Zhou, Wanpeng Zhang
Journal of System Simulation
Abstract: The development of artificial intelligence technology has greatly promoted the transformation of the solving paradigm of intelligent game decision problems. From optimal solution, equilibrium solution to adaptive variable solution, how to build an intelligent game adaptive decision agent based on generative large model is full of challenges. The force distribution and multi-entity coordination in the game strong confrontation environment are the core issues in the study of troop deployment and operational coordination. Based on the methods of strategy reinforcement learning, strategy game tree search and strategy preference voting based on skill, ranking and preference meta-game model construction, a large …
Method For Dynamic Coalition Formation Of Wargame Agent For Force Cooperation,
2025
School of Electronic & Information Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, China
Method For Dynamic Coalition Formation Of Wargame Agent For Force Cooperation, Changhua Yao, Shanning Bi, Rufei Ma, Xiaohan Yu, Jiaqiang Li, Jinli Chen
Journal of System Simulation
Abstract: Regarding the issue of cooperative task alliance formation and adjustment in multi-agent dynamic confrontation scenarios at the tactical level, this method comprehensively considers factors such as target value, task allocation, and operator characteristics, as well as the benefits and costs of executing different types of tasks. we propose a targeted force coordination adjustment for dynamic task alliance formation based on behavioral constraints. The “MiaoSuan-Wise Winning Instant Strategy Human-Computer Confrontation Platform” of Chinese Academy of Sciences (CAS) is used as an experimental platform to conduct confrontation experiments. The experiment demonstrates that the proposed method improves the dynamic coordination ability of …
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 …
Hierarchical Optimal Scheduling Of Integrated Energy System With Electric Vehicles Based On Empc,
2025
School of Control and Computer Engineering, North China Electric Power University, Beijing 102206, China; State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing 102206, China
Hierarchical Optimal Scheduling Of Integrated Energy System With Electric Vehicles Based On Empc, Miaomiao Ma, Zijuan Long, Zhiwei Ren, Yongqiang Cheng
Journal of System Simulation
Abstract: A hierarchical real-time optimization (HRTO) based on economic model predictive control is designed to address the issues of randomness and uncertainty of renewable energy and demand-side in integrated energy systems (IES) with electric vehicles. The optimization problem of the entire system is divided into three sub-problems: day-ahead rolling optimization, real-time rolling optimization, and tracking control. The day-ahead optimization strategy based on economic model predictive control is constructed to ensure that the operational units can meet users' demands. The optimal steady-state operating points of the entire IES are obtained through the real-time optimization layer. The tracking model predictive controller is …
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 …
Improved Hybrid Optimization Algorithm For Multi-Objective Ipps Problem,
2025
School of Mechanical and Electrical Engineering, Hohai University, Changzhou 213200, China
Improved Hybrid Optimization Algorithm For Multi-Objective Ipps Problem, Wenbin Gu, Jiexia Qing, Jie Fang, Siqi Liu
Journal of System Simulation
Abstract: For the problem of multi-objective integrated process planning and scheduling (MOIPPS), an improved hybrid optimization algorithm considering global and local optimum is proposed to optimize two objectives about minimum makespan and energy consumption. A multi-objective problem model and solution framework are established by analyzing the difference and connection between process planning and scheduling in integrated system. A hybrid optimization algorithm is proposed for the two-stage integration problem. In the process planning stage, global search algorithm is employed to provide a variety of process schemes for the integrated system and to ensure the global search performance of the integrated algorithm. …
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 Decision-Making Of Autonomous Driving In Highway Environment Based On Knowledge And Large Language Model,
2025
Department of computer science and technology, Dalian University of Technology, Liaoning 116081, China
Research On Decision-Making Of Autonomous Driving In Highway Environment Based On Knowledge And Large Language Model, Xiang Wang, Guozhen Tan
Journal of System Simulation
Abstract: Aiming at the lack of continuous learning and interpretability of current autonomous driving system, a decision model with cognition, generalization and learning ability is proposed. The model utilizes large language model (LLM) and attention mechanisms to understand and explain driving scenes. the system can accumulate and learn from driving experiences, continuously improving its decisionmaking ability. In a simulation environment, the closed-loop test decision model is applied in high-speed scenarios.The simulation results show that the success rate of the knowledge-driven model is 7% and 4% higher than those of the rule-based and data-driven methods. Additionally, the model exhibits generalization and …
Robot Path Planning Based On Ant Colony Algorithm With Dual Heuristic Information,
2025
Institute of Automation, Qilu University of Technology (Shandong Academy of Sciences), Jinan 250014, China
Robot Path Planning Based On Ant Colony Algorithm With Dual Heuristic Information, Xiaohui Zhou, Yanqiang Li, Yong Wang, Decai Zhao, Xiaoyao Yang
Journal of System Simulation
Abstract: The traditional ant colony algorithm is characterized by a slow convergence speed, numerous turning points, and a tendency to fall into local minima. These characteristics make the algorithm less effective for path planning research in mobile robotics. Therefore, this paper proposes an improved ant colony algorithm and applies it to global path planning for robots. The A* algorithm is used to quickly plan a path and increase the initial pheromone of that path, so that the improved algorithm is guided by the global path during the local search, preventing excessive ants from entering dead ends, and reducing the randomness …
