Garage Agv Path Planning And Simulation Based On Improved Dwa,
2024
College of Information and Control Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China
Garage Agv Path Planning And Simulation Based On Improved Dwa, Zongfang Ma, Linxuan Zhang, Lin Song, Jia Wang
Journal of System Simulation
Abstract: Aiming at the path planning and real-time obstacle avoidance of AGV in complex path environment of intelligent garage, an improved hybrid algorithm combining ant colony algorithm and dynamic window method is proposed. In the global planning, the adaptive adjustment of pheromone volatilization coefficient and the fusion of angle parameters are introduced to establish the garage direction pheromone matrix to increase the guidance ability of target points, expand the direction selectivity of ants. In the local planning, the improved DWA of the obstacle distance evaluation subfunction based on elliptic equation is designed. By extracting the global path node of the …
Adaptive Tracking Control For Omnidirectional Vehicle Based On Characteristic Modeling,
2024
Institute of Robotics and Intelligent Systems, Wuhan University of Science and Technology, Wuhan 430081, China
Adaptive Tracking Control For Omnidirectional Vehicle Based On Characteristic Modeling, Lei Cheng, Haoyou Wang, Xinjie Chen
Journal of System Simulation
Abstract: Aiming at the stable and high-precision tracking control of omnidirectional mobile vehicles affected by their own characteristics and external disturbances, an adaptive tracking control approach for omnidirectional vehicles based on characteristic modeling is designed. The characteristic model is established by integrating the model properties into the characteristic parameters, and the characteristic parameters are estimated online by using the projected gradient method. A full coefficient adaptive control law based on the characteristic model is designed, and the stability of the proposed control method is analyzed by using Lyapunov theory. The effectiveness and rationality of the proposed adaptive control scheme are …
Modeling Method Of Blue Army Warship Formation Air Defense Command And Control For System-Of-Systems Simulation,
2024
Shanghai Electro-Mechanical Engineering Institute, Shanghai 201109, China
Modeling Method Of Blue Army Warship Formation Air Defense Command And Control For System-Of-Systems Simulation, Shikang Chen, Zhimin Wang, Biao Liang, Kunren Gu, Keman Song, Yuan Gao
Journal of System Simulation
Abstract: The command and control of warship formation air defense is a key link for the blue army's sea to air combat tasks and the modeling of air defense for warship formation is an important component of simulation modeling of blue army's maritime combat system. Based on the background of system-of-systems simulation, the air defense command and control modeling for blue army is designed. Through a modular modeling method, functional module including asset management and plan, unified situation generation, command decision are designed. According to blue army's command and control logic, these modules are integrated and the air defense command …
Search Technology For Aircraft Debris Integrating Data Augmentation And Deep Learning Algorithm,
2024
Science and Technology on Space Physics Laboratory, Beijing 100076, China
Search Technology For Aircraft Debris Integrating Data Augmentation And Deep Learning Algorithm, Zhe Yang, Yinghan Cui, Lingxi Guo, Jiaxin Li, Xusheng Wu
Journal of System Simulation
Abstract: The reliable recovery of aircraft debris is of great significance for the complete acquisition of flight test data and the subsequent research and development of models. To ensure the safety of flight tests,the landing area of aircraft experiments is generally an unmanned area,and the actual landing point of the aircraft often deviates from the theoretical landing point. The characteristics of the debris target are complex and the dispersion area is large, making it difficult to search for aircraft debris solely by manpower. Aiming at the difficult problem of aircraft debris recovery in the landing area, through on UAV platforms …
Two-Level Optimal Dispatch Of Power System Based On Load-Storage Carbon Flow Model,
2024
State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Baoding 071003, China; Key Laboratory of Distributed Energy Storage and Microgrid of Hebei Province, North China Electric Power University, Baoding 071003, China
Two-Level Optimal Dispatch Of Power System Based On Load-Storage Carbon Flow Model, Yang Yu, Yuxing Xia, Wentao Lu, Mai Liu, Shixu Gao, Dongyang Chen
Journal of System Simulation
Abstract: In order to reduce the output of high energy consuming units on the power generation side, increase the absorption capacity of wind power, and consider the flexible resource allocation such as load and energy storage, a two-level economic low-carbon optimal scheduling method for power systems based on a carbon storage and discharge model is proposed. Based on the carbon emission flow theory of power system, a model for load and energy storage equipment is established; A demand response model based on the electricity carbon coupling price is established on the load side, and in view of the limitation on …
Research On Flexible Operational Optimization Of Cchp System Based On Intelligent Fusion Algorithm,
2024
Environmental Science and Engineering, North China Electric Power University College, Beijing 102206, China
Research On Flexible Operational Optimization Of Cchp System Based On Intelligent Fusion Algorithm, Zhe Bao, Xiaofang Zhang, Wei Li, Ye Xu, Xu Wang
Journal of System Simulation
Abstract: To further improve the accuracy of gas turbine simulation models, based on the construction of a gas turbine mechanism simulation model and BP simulation model, through model substitution technology and BP neural network algorithm three intelligent fusion simulation models for gas turbines, and two intelligent fusion simulation models for parallel gas turbines are constructed respectively as well as the combination of, by comparing the simulated results of the above models with the actual operating data, the simulation model with the best performance was selected. Using the intelligent fusion simulation model of the gas turbine as the output constraint, a …
Chaotic-Encode Quantum Pso Algorithm For Flexible Job-Shop Scheduling Problem,
2024
School of Electrical Engineering, Guizhou University, Guiyang 550025, China
Chaotic-Encode Quantum Pso Algorithm For Flexible Job-Shop Scheduling Problem, Yuanxing Xu, Mengjian Zhang, Deguang Wang
Journal of System Simulation
Abstract: To solve the flexible job-shop scheduling problem (FJSP), a chaotic-encode quantum PSO (CQPSO) algorithm is proposed. Aiming at the premature convergence of particles to local optimum in standard QPSO, the methods for computing the adaptive contraction-expansion coefficient and mean best position using fitness values of associated particles are proposed to improve the global search ability of QPSO. Through chaotic boundary variation strategy, the probability of a large number of particles gathering at the boundary is reduced and the population diversity is increased to enhance the ability of searching the optimal solution. According to the iterative property of QPSO, a …
Multi-Strategy Partheno-Genetic Algorithm Based On Dynamic Reduction Mechanism For Solving Cvrp Problem,
2024
School of Mathematics and Information , China West Normal University, Nanchong 637009, China
Multi-Strategy Partheno-Genetic Algorithm Based On Dynamic Reduction Mechanism For Solving Cvrp Problem, Jiajun Chen, Dailun Tan
Journal of System Simulation
Abstract: Aiming at the problems of premature, slow convergence and low accuracy of traditional genetic algorithm in solving capacitated vehicle routing problem,a multi-strategy partheno-genetic algorithm based on dynamic reduction mechanism is proposed. The algorithm divides the optimization space based on similar individuals, and uses simulated annealing criterion to eliminate or update the lowest category subspace, which constitutes the reduction and movement mechanism of the optimization space. Based on parthenogenetic algorithm,a variety of genetic evolution strategies including intra-group, inter-group, global search, disturbance and jump strategy are designed Based on the three penalty factors of individual development, population evolution and overall convergence, …
Unmanned Vehicle Path Planning And Tracking Control Based On Improved Artificial Potential Field Method,
2024
School of Mechanical and Equipment Engineering, Hebei University of Engineering, Handan 056038, China
Unmanned Vehicle Path Planning And Tracking Control Based On Improved Artificial Potential Field Method, Minghao Guo, Peng Ji, Haiwei Huang
Journal of System Simulation
Abstract: A path planning algorithm based on improved artificial potential field method and a tracking control strategy based on model predictive controller are proposed for the unmanned vehicle avoiding dynamic obstacles in the complex scene of lane changing and overtaking. The theory of safety ellipse and the concept of prediction distance are introduced to adjust the influence region of potential field. By adding velocity potential field to change potential field function, the problem of vehicle avoiding dynamic obstacles is solved. Based on the linear three-degree-of-freedom vehicle dynamics model, a model prediction controller including potential field environment is established. The effectiveness …
Path Following Control And Simulation Analysis Of Multi-Articulated Vehicles,
2024
State Key Laboratory of Rail Transit Vehicle System, Southwest Jiaotong University, Chengdu 610031, China
Path Following Control And Simulation Analysis Of Multi-Articulated Vehicles, Yu Zhao, Caijin Yang, Tanming Wang, Jing Xu, Shuai Zhou
Journal of System Simulation
Abstract: The structure of multi-articulated vehicle body limits the flexibility of the vehicle and causes the deviation of the rear vehicle. Taking the ideal articulation angle as the control target, a feedforward plus feedback path following control method is proposed, which realizes the precise path following of rear vehicle bodies by minimizing the deviation between the ideal articulation angle and the actual articulation angle. According to the geometric position relationship between the vehicle and the desired path, the traditional calculation method of the ideal articulation angle is improved from two perspectives of application range and error accumulation. Based on the …
Improved Foggy Pedestrian And Vehicle Detection Algorithm Based On Yolov5,
2024
School of Information Engineering, Nanchang Institute of Technology, Nanchang 330000, China
Improved Foggy Pedestrian And Vehicle Detection Algorithm Based On Yolov5, Tong Su, Ying Wang, Qiyang Deng, Zhaobin Li
Journal of System Simulation
Abstract: Due to the poor environment perception of car in bad weather, the detection ability on dynamic targets is significantly reduced, and thus the problems such as low accuracy and poor robustness of the deep learning-based target detection network will occur when detecting pedestrians and vehicles in foggy days. A YOLOv5-SGE foggy detection network is proposed on the basis of the combination of image dehazing DehazeNet and the improved YOLOv5. The adaptive calculation of anchor frame is realized by canceling the initial anchor frame of YOLOv5, and the anchor frame suitable for the current dataset is generated. A three-dimensional weighted …
A Method For Battlefield Situation Information Ontology Construction Based On Top-Down And Bottom-Up Integration,
2024
College of Intelligence Science and Technology, National University of Defense Technology, Changsha 410000, China
A Method For Battlefield Situation Information Ontology Construction Based On Top-Down And Bottom-Up Integration, Cong Zhou, Sihang Zhou, Jian Huang, Dong Wang
Journal of System Simulation
Abstract: The construction of the unified expression model of battlefield situational information is challenging due to the complexity of data sources and the significant differences in data structures and expression methods. Ontologies, as semantic conceptual models, are often used to describe concepts, relationships, and attributes within knowledge domains. An ontology construction method for the battlefield situational information domain based on a top-down and bottom-top integration is proposed. The top-down method is used to construct the upper ontology, in which a conceptual hierarchy model with a clear top-down structure is designed to establish the hierarchical relationships and semantic associations. A bottom-up …
Peer-To-Peer Energy-Carbon Management Method Of Multiple Integrated Energy Systems Considering Multi-Agent Interaction Strategy,
2024
State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources (North China Electric Power University), Beijing 102206, China
Peer-To-Peer Energy-Carbon Management Method Of Multiple Integrated Energy Systems Considering Multi-Agent Interaction Strategy, Yudong Wang, Junjie Hu
Journal of System Simulation
Abstract: To explore a new energy management model of P2P transaction of electricity, heat and carbon among IES with the participation of ESP, a P2P energy-carbon management method of IES considering multi-agent interaction strategy is proposed. A two-layer energy management framework with the multiagent participation of involving ESP and IES is established. A two-layer electricity-heat-carbon energy management model is constructed in which the upper model is constructed based on reinforcement learning framework to optimize the energy management strategy between ESP and IES cooperative alliance and the lower model is based on Nash negotiation game theory to optimize the cooperative operation …
Solubility Characterization Of Organic Molecules For Aqueous Organic Redox Flow Batteries,
2024
California Polytechnic State University, San Luis Obispo
Solubility Characterization Of Organic Molecules For Aqueous Organic Redox Flow Batteries, Anthony W. Ferrell, Harkeerith K. Vij, Seamus D. Jones
College of Engineering Summer Undergraduate Research Program
The major obstacle to renewable energy sources is a lack of long-term energy storage capabilities. Energy produced during the day dissipates, leaving insufficient electricity for at night. The goal of the project is to design an Aqueous Organic Redox Flow Battery (AORFB) to act as long-term energy storage. Work has been done using machine learning to identify suitable compounds for the batteries. In this work there was no indication as to the aqueous solubility of the molecules; this controls the device’s energy storage capabilities. We used a machine learning model to determine the aqueous solubility of slightly more than 3000 …
Leveraging Tradespace-Exploration For A Senior Project Team Formation Application,
2024
California Polytechnic State University, San Luis Obispo
Leveraging Tradespace-Exploration For A Senior Project Team Formation Application, Miguel Saenz
College of Engineering Summer Undergraduate Research Program
This project revolves around the development of an app in MATLAB that leverages the VASSAR rule-based system and a genetic algorithm to form groups of teams for the Mechanical Engineering Senior Design project class. We leveraged the iterative design process to eventually attain a functional app with a reasonable runtime that works provided correctly formatted rulesheets describing student project preference and member preference.
Joint Weakly Supervised Image Emotion Analysis Based On Interclass Discrimination And Intraclass Correlation,
2024
Singapore Management University
Joint Weakly Supervised Image Emotion Analysis Based On Interclass Discrimination And Intraclass Correlation, Xinyue Zhang, Zhaoxia Wang, Guitao Cao, Seng-Beng Ho
Research Collection School Of Computing and Information Systems
Regional information-based image emotion analysis has recently garnered significant attention. However, existing methods often focus on identifying region proposals through layered steps or merely rely on visual saliency. These approaches may lead to an underestimation of emotional categories and a lack of comprehensive interclass discrimination perception and emotional intraclass contextual mining. To address these limitations, we propose a novel approach named InterIntraIEA, which combines interclass discrimination and intraclass correlation joint learning capabilities for image emotion analysis. The proposed method not only employs category-specific dictionary learning for class adaptation, but also models intraclass contextual relationships and perceives correlations at the channel …
Efficient Cascaded Multiscale Adaptive Network For Image Restoration,
2024
Singapore Management University
Efficient Cascaded Multiscale Adaptive Network For Image Restoration, Yichen Zhou, Pan Zhou, Teck Khim Ng
Research Collection School Of Computing and Information Systems
Image restoration, encompassing tasks such as deblurring, denoising, and super-resolution, remains a pivotal area in computer vision. However, efficiently addressing the spatially varying artifacts of various low-quality images with local adaptiveness and handling their degradations at different scales poses significant challenges. To efficiently tackle these issues, we propose the novel Efficient Cascaded Multiscale Adaptive (ECMA) Network. ECMA employs Local Adaptive Module, LAM, which dynamically adjusts convolution kernels across local image regions to efficiently handle varying artifacts. Thus, LAM addresses the local adaptiveness challenge more efficiently than costlier mechanisms like self-attention, due to its less computationally intensive convolutions. To construct a …
Does Ceo Agreeableness Personality Mitigate Real Earnings Management?,
2024
Singapore Management University
Does Ceo Agreeableness Personality Mitigate Real Earnings Management?, Shan Liu, Xingying Wu, Nan Hu
Research Collection School Of Computing and Information Systems
Despite efforts to mitigate aggressive financial reporting, earnings management remains challenging to parties interested in inhibiting its dysfunctional effects. Using linguistic algorithms to assess CEO agreeableness personality from their unscripted texts in conference calls, we find that it is a determinant that mitigates a firm's real earnings management. Furthermore, such an effect is more pronounced when firms confront intensive market competition and financial distress and have weaker managerial entrenchment or when CEOs face stronger internal governance. Our findings persist even after we utilize several alternative real earnings management metrics and control other confounding personalities in prior earnings management studies. The …
Motif Graph Neural Network,
2024
Guangdong University of Technology
Motif Graph Neural Network, Xuexin Chen, Ruicui Cai, Yuan Fang, Min Wu, Zijian Li, Zhifeng Hao
Research Collection School Of Computing and Information Systems
Graphs can model complicated interactions between entities, which naturally emerge in many important applications. These applications can often be cast into standard graph learning tasks, in which a crucial step is to learn low-dimensional graph representations. Graph neural networks (GNNs) are currently the most popular model in graph embedding approaches. However, standard GNNs in the neighborhood aggregation paradigm suffer from limited discriminative power in distinguishing high-order graph structures as opposed to low-order structures. To capture high-order structures, researchers have resorted to motifs and developed motif-based GNNs. However, the existing motif-based GNNs still often suffer from less discriminative power on high-order …
Large-Scale Graph Label Propagation On Gpus,
2024
Singapore Management University
Large-Scale Graph Label Propagation On Gpus, Chang Ye, Yuchen Li, Bingsheng He, Zhao Li, Jianling Sun
Research Collection School Of Computing and Information Systems
Graph label propagation (LP) is a core component in many downstream applications such as fraud detection, recommendation and image segmentation. In this paper, we propose GLP, a GPU-based framework to enable efficient LP processing on large-scale graphs. By investigating the data processing pipeline in a large e-commerce platform, we have identified two key challenges on integrating GPU-accelerated LP processing to the pipeline: (1) programmability for evolving application logics; (2) demand for real-time performance. Motivated by these challenges, we offer a set of expressive APIs that data engineers can customize and deploy efficient LP algorithms on GPUs with ease. To achieve …
