Research Progress Of Opponent Modeling Based On Deep Reinforcement Learning,
2023
College of Systems Engineering, National University of Denfense Technology, Changsha 410073, China;
Research Progress Of Opponent Modeling Based On Deep Reinforcement Learning, Haotian Xu, Long Qin, Junjie Zeng, Yue Hu, Qi Zhang
Journal of System Simulation
Abstract: Deep reinforcement learning is an agent modeling method with both deep learning feature extraction ability and reinforcement learning sequence decision-making ability, which can make up for the depleted non-stationary adaptation, complex feature selection and insufficient state-space representation ability of traditional opponent modeling. The deep reinforcement learning-based opponent modeling methods are divided into two categories, explicit modeling and implicit modeling, and the corresponding theories, models, algorithms and applicable scenarios are sorted out according to the categories. The applications of deep reinforcement learning-based opponent modeling techniques on different fields are introduced. The key problems and future development are summarized to provide …
Dynamic Target Assignment Of Multiple Unmanned Aerial Vehicles Based On Clustering Of Network Nodes,
2023
School of Mechatronic Engineering and Automation, National University of Defense Technology, Changsha 410003, China;
Dynamic Target Assignment Of Multiple Unmanned Aerial Vehicles Based On Clustering Of Network Nodes, Tuo Zhao, Hanqiang Deng, Jialong Gao, Jian Huang
Journal of System Simulation
Abstract: In order to solve the problem that the distributed multi-UAV target assignment algorithm is prone to communication redundancy, which leads to the large communication scale of formation, a multi-UAV dynamic target assignment algorithm (CU-CBBA) based on node clustering in communication network is proposed.The algorithm introduces the communication network node grouping clustering strategy. According to the node's degree centrality, feature vector centrality, intermediate centrality and other attributes, the network node importance ranking model is established. A group of key nodes in the network topology structure are selected and the network topology node clustering is completed according to the shortest …
Adaptive Correction Tracking Algorithm Based On Detector And Locator Fusion,
2023
School of Electronic and Information Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China;
Adaptive Correction Tracking Algorithm Based On Detector And Locator Fusion, Yecai Guo, Cheng Liu
Journal of System Simulation
Abstract: In order to avoid tracking failure caused by occlusion, rotation and other factors in complex dynamic scenes, an adaptive correction tracking algorithm based on detector and locator fusion is proposed. The locator trains a convolutional neural network (CNN) filter for location estimation by extracting the deep features of target. The CNN filter adds two layers of shallow features to the three layers of the convolution features of original CF2 algorithm, which enhances the extraction of target texture information. The detector calculates the confidence score by extracting histogram of oriented gradient(HOG) feature of target and combining the context information. …
Cross-Domain Text Sentiment Classification Based On Auxiliary Classification Networks,
2023
1.School of Business Administration, Liaoning Technical University, Huludao 125105, China;
Cross-Domain Text Sentiment Classification Based On Auxiliary Classification Networks, Na Ma, Tingxin Wen, Xu Jia, Xiaohui Li
Journal of System Simulation
Abstract: To align exactly the texts with same sentiment polarities of source and target domains, and to enlarge the feature difference of different sentiment texts as much as possible, a domain adaptation model with weighted adversarial networks is proposed. A new structured classification network consisting of a main classification network and an auxiliary classification network is proposed, in which the main classification network is used to perform supervised learning on the labeled texts of the source domain, and the auxiliary classification network is used to improve the distinguishability of the text features. A calculation method of multiple adversarial network weights …
Trajectory Control Of Crawler Robot Based On Lstm And Smc,
2023
School of Information and Computer, Anhui Agricultural University, Hefei 230036, China;
Trajectory Control Of Crawler Robot Based On Lstm And Smc, Dongyang Liu, Wenwen Zha, Liang Tao, Cheng Zhu, Lichuan Gu, Jun Jiao
Journal of System Simulation
Abstract: Trajectory tracking is an important part of mobile robot control technology and possesses prospect. Highly nonlinear dynamic characteristics are the main obstacles of controller design. A SMC method based on LSTM and quasi-sliding mode is proposed. The kinematics model and dynamics model of the tracked vehicle are given, and the sliding mode control system is established based on the dynamics model. LSTM network based on deep learning method is designed to control and compensate the unknown interference items, reduce the influence of external interference, and reduce the tremor phenomenon by combining the advantages of LSTM network and quasi-sliding …
Knowledge Graph-Based Process Knowledge Reasoning Method For Intelligent Production System,
2023
Engineering Research Center of Internet of Things Technology Applications Ministry of Education, Jiangnan University, Wuxi 214122, China;
Knowledge Graph-Based Process Knowledge Reasoning Method For Intelligent Production System, Weikai Yang, Yan Wang, Zhicheng Ji
Journal of System Simulation
Abstract: Aiming at the disadvantages of high redundancy and weakness between knowledge and data in intelligent production system, and the difficulty to perform knowledge reasoning, a process knowledge reasoning method for knowledge maps is proposed. The input information is semantically labeled and classified, the characteristics of the information match are extracted, the extracted local feature and global feature are associated through graph convolution method, and the feature of the difference value information is integrated and mapped with the constructed knowledge graph. Different reasoning rules are used according to different reasoning types, and the association and topology information between instances are …
Multi-Agent Cooperative Combat Simulation In Naval Battlefield With Reinforcement Learning,
2023
School of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing 211100, China;
Multi-Agent Cooperative Combat Simulation In Naval Battlefield With Reinforcement Learning, Ding Shi, Xuefeng Yan, Lina Gong, Jingxuan Zhang, Donghai Guan, Mingqiang Wei
Journal of System Simulation
Abstract: Due to the rapidly-changed situations of future naval battlefields, it is urgent to realize the high-quality combat simulation in naval battlefields based on artificial intelligence to comprehensively optimize and improve the combat effectiveness of our army and defeat the enemy. The collaboration of combat units is the key point and how to realize the balanced decision-making among multiple agents is the first task. Based on decoupling priority experience replay mechanism and attention mechanism, a multi-agent reinforcement learning-based cooperative combat simulation (MARL-CCSA) network is proposed. Based on the expert experience, a multi-scale reward function is designed, on which a naval …
I-Nicemo Enhanced Algorithm Based On Intersection Angel Geometry,
2023
1.College of Computer Science and Software Engineering, Shenzhen University, Shenzhen 518060, China;
I-Nicemo Enhanced Algorithm Based On Intersection Angel Geometry, Yifan He, Yulin He, Yongda Cai, Zhexue Huang
Journal of System Simulation
Abstract: To exactly determine the number of cluster centers and correctly identify the candidate cluster centers, an I-niceMO enhanced(I-niceMOEn) algorithm based on intersection angel geometry is proposed. As many distributions of intersection angles and distances as possible between observation points and data points are utilized to recognize the candidate cluster centers to avoid the neglection of cluster centers. The spectral clustering algorithm is used to automatically merge the candidate cluster centers according to the eigenvalues of Laplacian matrices. The number of final cluster centers is determined by the number of merged candidate cluster centers. The number of clusters can be …
Bottleneck Drift Fluctuation Analysis Of Discrete Remanufacturing System Under Disturbance,
2023
Engineering Research Center of Internet of Things Technology Applications Ministry of Education, Jiangnan University, Wuxi 214122, China;
Bottleneck Drift Fluctuation Analysis Of Discrete Remanufacturing System Under Disturbance, Yongzhang Zhou, Yan Wang, Zhicheng Ji
Journal of System Simulation
Abstract: Considering comprehensively the influence of each production process on the bottleneck degree of discrete remanufacturing system, the interval bottleneck index matrix is established by collecting data repeatedly in the observation stage to obtain the comprehensive bottleneck index of equipment, which is used as the identification basis. Aiming at the volatility of bottleneck drift in the uncertain environment of discrete remanufacturing system, based on the interval bottleneck index matrix and comprehensive bottleneck index, a theoretical method of visual dynamic analysis including system sensitivity coefficient, machine sensitivity coefficient and bottleneck drift judgment model is established. The discrete event simulation case is …
Shared Subnet Synthesis And Application Of Object-Oriented Pres Net,
2023
College of Computer Science and Technology, Shandong Jianzhu University, Ji?nan 250101, China;
Shared Subnet Synthesis And Application Of Object-Oriented Pres Net, Chuanliang Xia, Maibo Guo, Zhuangzhuang Wang, Yan Sun
Journal of System Simulation
Abstract: Focus on embedded system modeling, a solution to obtain a synthesized net via the shared subnet of an extended Petri net is proposed. Object-oriented technology and Petri net-based representation for embedded system (PRES net) are merged to obtain an object-oriented PRES net (OOPRES net). A method of synthesized operation of the shared subnet of OOPRES net is proposed, and the preservation of the liveness and boundedness of synthesized net system is studied. Taking the modeling analysis of intelligent transportation system as an example, the effectiveness of the synthesized method is verified. The method can provide an effective way for …
Construction Technology Of Hand Posture Dataset Based On Virtual Simulation Method,
2023
Harbin Normal University, Harbin 150080, China;
Construction Technology Of Hand Posture Dataset Based On Virtual Simulation Method, Jiaxin Chen, Guohui Zhou, Jianbai Yang
Journal of System Simulation
Abstract: Hand posture is an important carrier of human-computer interaction, and the acquisition and recognition of posture information largely depends on the hand posture dataset. Existing datasets can be divided into two categories, real datasets and synthetic datasets. As real data is limited by equipment, environment, and other factors, the classification of hand posture is insufficient and the annotation is mixed with a lot of manual errors. The existing synthetic data can solve the data scale problem of real data, but the synthetic hand posture volume is limited and with some unreasonable kinematic postures of which the data form are …
Research On Improvement Of Social Force Model Based On Non-Motor Vehicle Active Overtaking Behavior,
2023
1.Civil and Transportation Engineering College, Beijing University of Civil Engineering and Architecture, Beijing 100044, China;3.Beijing University of Civil Engineering and Architecture, Beijing Urban Transportation Infrastructure Engineering and Architecture, Beijing 100044, China;
Research On Improvement Of Social Force Model Based On Non-Motor Vehicle Active Overtaking Behavior, Minghui Yang, Rui Zhang, Qiaobing Yan, Jiahe Wang
Journal of System Simulation
Abstract: Aiming at the social force model not to illustrate the active overtaking behavior of the rear non-motor vehicle to the front vehicle, an improved social force model is proposed. The traffic behavior characteristics of non-motorized vehicles mixed flow during the active overtaking is analyzed. Considering the compressible characteristics of non-motorized vehicle distancing in different density environments, the model is improved by presenting the concept of dynamic perception space and introducing the overtaking force into the social force model. The model is verified by analyzing the active overtaking behavior, active overtaking distance and speed-density basic graphs. The results indicate that …
Research On Unmanned Swarm Combat System Adaptive Evolution Model Simulation,
2023
1.Joint Operation Institute, National Defense University, Beijing 100091, China;
Research On Unmanned Swarm Combat System Adaptive Evolution Model Simulation, Zhiqiang Li, Yuanlong Li, Laixiang Yin, Xiangping Ma
Journal of System Simulation
Abstract: Aiming at the fact that the intelligent unmanned swarm combat system is mainly composed of large-scale combat individuals with limited behavioral capabilities and has limited ability to adapt to the changes of battlefield environment and combat opponents, a learning evolution method combining genetic algorithm and reinforcement learning is proposed to construct an individual-based unmanned bee colony combat system evolution model. To improve the adaptive evolution efficiency of bee colony combat system, an improved genetic algorithm is proposed to improve the learning and evolution speed of bee colony individuals by using individual-specific mutation optimization strategy. Simulation experiment on …
Atmospheric Corrosion Simulation Of Air Conditioning Heat Exchanger In Service Under Marine Environment,
2023
State Key Laboratory of Environmental Adaptability for Industrial Products, China National Electric Apparatus Research Institute Co. , Ltd. , Guangzhou 510663, China;
Atmospheric Corrosion Simulation Of Air Conditioning Heat Exchanger In Service Under Marine Environment, Huang Peng, Jun Wang, Li Qi, Zhidong Wu
Journal of System Simulation
Abstract: Aiming at the performance degradation of airconditioner heat exchanger caused by serious corrosion under marine environment, an atmospheric corrosion simulation method is studied to analyze and predict the influence on corrosion conditions of marine environment and working condition of air conditioner heat exchanger. From the acquisition of material parameters, the construction the model and the setting of boundary conditions, the atmospheric corrosion simulation process of air conditioner heat exchanger in service under marine environment is systematically introduced, and a method to verify the accuracy of the simulation model by using an artificially accelerated environmental test chamber is provided. From …
Dual Resource Constrained Flexible Job Shop Energy-Saving Scheduling Considering Delivery Time,
2023
1.Key Laboratory of Multidisciplinary Management and Control of Complex Systems of Anhui Higher Education Institutes (Anhui University of Technology), Ma'anshan 243032, China;2.School of Management Science and Engineering, Anhui University of Technology, Ma'anshan 243032, China;
Dual Resource Constrained Flexible Job Shop Energy-Saving Scheduling Considering Delivery Time, Hongliang Zhang, Jingru Xu, Bo Tan, Gongjie Xu
Journal of System Simulation
Abstract: To handle the flexible job shop energy-saving scheduling with machines and workers constraints, on the considering of delivery time, the optimization model of dual resource constrained flexible job shop energy-saving scheduling is established with the goal of minimizing the total earliness and tardiness penalties, and total energy consumption. An improved non-dominated sorting genetic algorithm II(INSGA-II) is proposed. Aiming at the optimized objectives, a three-stage decoding method is designed to gain more feasible solutions. The dynamic adaptive crossover and mutation operators are applied to get more excellent individuals. The crowding distance is improved to obtain a population with better …
Research On Workshop Logic Modeling And Simulation Based On Finite State Machine,
2023
School of Mechanical Engineering, Southwest Jiaotong University, Chengdu 610031, China;
Research On Workshop Logic Modeling And Simulation Based On Finite State Machine, Mingyuan Liu, Jiaxiang Xie, Hao Wu, Jianlin Fu, Guofu Ding
Journal of System Simulation
Abstract: Discrete manufacturing is common in aircraft, ships, electronic equipment, automobile and other manufacturing industries. To ensure the correctness and flexibility of the modeling and simulation process of discrete manufacturing workshops, a logical modeling and simulation method for the production process of discrete manufacturing workshop is proposed. Based on the theory of discrete event dynamic systems and finite-state machines, the attributes and behaviors of the key elements of the discrete manufacturing workshop are abstracted into a unified logic model, and the function of various elements are realized through inheritance. A production process simulation algorithm is designed for the unified model …
Dynamics Modeling And Online Prediction Of Energy Consumption Of Discrete Manufacturing System,
2023
School of Internet of Things Engineering, Jiangnan University, Wuxi 214122, China;
Dynamics Modeling And Online Prediction Of Energy Consumption Of Discrete Manufacturing System, Wei Chen, Yan Wang, Zhicheng Ji
Journal of System Simulation
Abstract: Aiming at the traditional energy consumption modeling methods of discrete manufacturing system being difficult to adapt to the complexity and variability of working conditions, an online dynamic energy consumption modeling method based on real-time data is proposed. The energy consumption affecting factors are determined by analyzing the operation mechanism of the discrete manufacturing system and equipment. An online sequential extreme learning machine algorithm that can dynamically adjust the number of hidden layer nodes is proposed to construct the energy consumption model. The real-time data can update the model quickly. Bernstein's inequality is introduced to improve the model data screening …
Utilizing The System Engineering Trade Study Analysis Method To Analyze Patient Aeromedical Evacuation,
2023
Air Force Institute of Technology
Utilizing The System Engineering Trade Study Analysis Method To Analyze Patient Aeromedical Evacuation, Sara Shaghaghi, Jeremy M. Slagley, Michael E. Miller, Gaiven Varshney
Faculty Publications
The US Air Force has gone through many aeromedical patient isolation transport system designs. The first designs were developed in response to the Ebola outbreak in 2014 and, more recently, the COVID-19 pandemic. The trade study analysis part of the system engineering design method was used to analyze the historic and current aeromedical patient contamination control transport systems. A trade study is a process that evaluates alternatives based upon various “-ilities”, such as reconfigurability, flexibility, durability, cost, and more, and performs a systematic analysis to aid designers in producing a ‘good’ design alternative given the large set of possible solutions. …
Systems Thinking As A Method For Leveraging Smart Classrooms,
2023
University of Texas at El Paso
Systems Thinking As A Method For Leveraging Smart Classrooms, Jazmyne V. Del Hierro
Open Access Theses & Dissertations
Digital technologies have revolutionized enterprises across our personal lives, and most major industries. The digital transformation can be considered a strategic response to digital trends (Vial, 2019), encompassing substantial changes in society and industry caused by technology development (Taj, et al., 2010). It is a complex journey that needs to be guided by clear strategy. Digital transformation is more about people, than it is about technology (Frankiewiczz, B., 2020). It requires organizational changes that are backed by leadership and driven by challenges to culture (Abbu, H., 2022). Digital transformation requires leaders to build trust (Mugge, Abbu, and Gudergan 2021; Gudergan …
Self-Learning Algorithms For Intrusion Detection And Prevention Systems (Idps),
2023
Southern Methodist University
Self-Learning Algorithms For Intrusion Detection And Prevention Systems (Idps), Juan E. Nunez, Roger W. Tchegui Donfack, Rohit Rohit, Hayley Horn
SMU Data Science Review
Today, there is an increased risk to data privacy and information security due to cyberattacks that compromise data reliability and accessibility. New machine learning models are needed to detect and prevent these cyberattacks. One application of these models is cybersecurity threat detection and prevention systems that can create a baseline of a network's traffic patterns to detect anomalies without needing pre-labeled data; thus, enabling the identification of abnormal network events as threats. This research explored algorithms that can help automate anomaly detection on an enterprise network using Canadian Institute for Cybersecurity data. This study demonstrates that Neural Networks with Bayesian …
